Prediction markets are still widely discussed as betting venues, places where people speculate on elections, sports, or headlines for entertainment and profit.

The interface reinforces the label: “Yes” or “No”, wait for resolution, win or lose.

But that framing is becoming increasingly incomplete. Prediction markets are evolving into something far more important: structured information-pricing systems, markets whose primary function is to translate dispersed beliefs, signals, and private knowledge into tradable probabilities that can be benchmarked, hedged against, and ultimately resolved against observable outcomes

The catalyst is fair value.

Why “Betting” Is the Wrong Frame

The “betting” label has always followed prediction markets for two reasons.

First, their early use cases were legible only as wagers: politics, sports, celebrity outcomes , events with clear resolution. Second, the contracts themselves resemble a binary bet: $1 if true, $0 if false.

But structurally, that contract is not a bet. It is a probability instrument: a tradable claim whose price encodes a collective estimate of likelihood, shaped by incentives, capital, and information.

When you call a prediction market a betting venue, three constraints appear:

• Legitimacy collapses. Regulators, institutions, and serious capital often treat “betting” as entertainment, not infrastructure. Even when the mechanism is rational, the framing invites skepticism.
• Participation narrows. Betting attracts a specific user profile: high-conviction traders, speculators, hobbyists. It discourages analysts, risk managers, researchers, and builders who would otherwise treat probabilities as inputs to real decisions.
• Market design stalls. If you think you’re building a casino, you optimize for engagement and volume. If you think you’re building an information-pricing system, you optimize for calibration, liquidity quality, integrity, and composability.

The betting frame doesn’t just affect perception. It affects what the market becomes.

How Fair Value Changes Participant Behavior

Prediction markets still feel like “bets” because most participants lack a reliable reference for what a contract should be worth.

At the simplest level, a prediction market contract is an expected value claim:

• Pays $1 if an event occurs
• Pays $0 if it does not
• Under a risk-neutral framework, fair value ≈ P (event)

Without fair value, users infer probability from price action and narrative. They trade vibes, react to attention, and overfit to the latest headline. Even sophisticated traders can end up anchored to the market itself, “the price must know something”, which reinforces herding.

When a credible fair value reference exists, the mindset shifts:

• “Is the market price above or below fair value?”
• “How strong is the evidence behind that estimate?”

That shift is subtle but transformative. Trading becomes less about conviction and more about mispricing detection.

• If Fair Value > Market Price → buy is statistically favorable
• If Fair Value < Market Price → sell is statistically favorable

Fair value makes probabilities operational. They become something you can act on with defined logic, not just interpret emotionally.

From Tradable Probabilities to Institutional-Grade Signals

Institutions adopt markets when they produce dependable inputs.

For prediction markets to function as information infrastructure, probability signals must be:

• reliable enough to benchmark decisions against
• consistent across categories and time horizons
• robust to manipulation, thin liquidity, and narrative volatility

When that bar is met, use cases compound:

Risk teams can use market probabilities as dynamic scenario weights. Researchers can compare model forecasts against a living probability reference. Treasuries can hedge event risk with clearer expected-value logic. Platforms can build products on top of a shared probability language rather than reinventing it per market.

This is also what drives maturity. Market maturity is not just “more volume.” It’s tighter pricing, more stable liquidity, and faster convergence toward fair value.

A trustworthy fair value reference accelerates maturation.

Liquidity providers can quote tighter spreads when they have a better anchor. Traders can arbitrage deviations more consistently. Markets converge faster because disagreements become quantifiable. Over time, pricing becomes less sensitive to hype and more sensitive to measurable information.

Fair value doesn’t eliminate volatility. But it changes volatility from chaos into signal, because deviations can be tracked, explained, and learned from.

Agent Participation and Agent-to-Agent Economies

The biggest  shift comes when AI agents become native participants.

Humans trade intermittently. Agents trade continuously.

Agents can monitor thousands of markets, update probabilities in real time, act on small mispricings, and record performance with mechanical discipline. As agents scale, the market evolves from “human debate with money attached” into probability computation at scale.

Eventually, this creates the foundation for agent-to-agent economies. Early prototypes of AI agents that consume and publish probabilistic signals already exist, but large‑scale agent‑to‑agent markets are still in the experimental and roadmap stage.

• agents consume probabilities via APIs as inputs
• agents publish probabilities as outputs with track records
• strategies and vaults allocate capital based on verifiable signals
• specialized agents compete on calibration, not charisma
• agents become modular services in a broader prediction stack

In that environment, probabilities stop being opinions. They become primitives that other systems can compose.

This is the real meaning of “information-pricing systems”: markets become computational substrates where uncertainty is continuously priced and scored.

Yala’s Vision for the Next Generation of Prediction Markets

Prediction markets don’t just need more participants. They need a fair value reference that is reliable, accessible, and verifiable over time.

Yala is building fair value intelligence for the prediction economy: an AI‑native fair‑value agent that generates calibrated probability references to make market pricing more interpretable, more testable, and ultimately more trustworthy.

As fair value becomes dependable, prediction markets change:

• from entertainment to infrastructure.
• from narratives to measurable probabilities.
• from isolated bets to composable decision inputs.
• from human-only participation to agent-native ecosystems.

The betting frame can fade, not because speculation disappears, but because the deeper function of these markets becomes clear. Fair value is the catalyst. 

Yala is building toward what comes next.

Yala is building what prediction markets are missing: a consistent, accessible fair value reference for probability pricing.

But fair value isn’t something you release once and call done. It’s something you construct progressively, validating each step through measurement.

This article outlines Yala’s multi-stage roadmap, explaining why the platform is being built incrementally, from early fair value signals to a full multi-agent probabilistic system, and how each phase de-risks the next.

Why Fair Value Systems Must Be Built in Stages

Most software allows you to ship version one and iterate. In probability systems, you don’t get that luxury.

Prediction markets surface collective intelligence, but they don’t automatically create a stable reference for fair value. In practice, prices can drift, not because markets “fail,” but because they operate under constraints: liquidity thins, narratives cascade, information is uneven, and timing effects can dominate short horizons. Without a calibration discipline, probability pricing becomes inconsistent across categories and environments.

Yala builds in stages to make calibration measurable. Each phase has clear objectives, operates within a defined risk envelope, and validates the assumptions of the previous one before advancing.

Early Stage: Methodology, Calibration, and Public Signals

The early stage focuses on establishing the foundations of fair value estimation. Yala conducts closed internal testing of early fair value estimation systems, generating probability outputs that are refined and evaluated before full autonomous agent deployment. During this phase, Yala also publishes a steady stream of probability signals through its official X account.

These signals are published primarily as methodological outputs: they make Yala’s fair value approach observable and scorable over time, before full agent deployment. By allowing these signals to resolve against real-world outcomes over time, the system builds an observable validation surface.

At this stage, Yala answers a narrow but essential question:

Can fair value be expressed consistently, so it can be measured, scored and improved?

This must be resolved before live trading and capital deployment become part of the validation loop.

Mid Stage: Autonomous Agents, Live Validation, Controlled Capital

If the early stage proves fair value can be expressed, the mid stage asks a harder question:

Can it hold up in real markets, under incentives?

This phase marks the public launch of Yala’s first fair value AI agent. As the system matures, Yala moves from publishing probability outputs to operating a live, empirically verifiable fair value agent designed for price prediction markets and risk-neutral valuation. The agent incorporates historical trading data alongside complementary signals such as news, smart-money flows, and sentiment, and operates under controlled market conditions.

Mid stage introduces the modular architecture: APIs, bot interfaces, and plug-and-play components, so fair value queries can be used across surfaces and extended across market types. It also introduces fair-value-driven live trading in a controlled environment, with intentionally limited capital to validate logic while enforcing strict risk constraints.

By the end of this stage, fair value is no longer a signal stream. It becomes a measurable agent behavior, continuously scored and refined through live market feedback.

Late Stage: Multi-Agent Systems and Cross-Domain Forecasting

Mid stage validates a single fair value agent. The late stage expands the design space:

Can fair value scale across domains, and across agents, without losing coherence?

In the late stage, Yala evolves into a multi-agent swarm system capable of cross-domain fair value evaluation. The system moves beyond a single valuation lens by coordinating specialized agents that contribute different perspectives: market structure, narrative dynamics, smart-money behavior, and other domain-specific signals, and aggregating them into unified probabilistic outputs.

Scope expands in four directions that matter most for the roadmap:

1/ From risk-neutral to subjective fair value, integrating contextual intelligence.

2/ From narrow market coverage to cross-domain forecasting.

3/ From single-point estimates to richer probabilistic structures with distributions and confidence intervals. 

4/ Toward privacy-aware, tokenized agent economies that use calibration and resolution as proof of validity.

At this stage, fair value is no longer evaluated as a single agent’s behavior, but as a system-level capability: a probabilistic backbone that markets, agents and users can coordinate on.

Measuring Success Across Stages

As Yala evolves from a single agent into a multi-agent system, complexity grows faster than certainty. At that point, the question is no longer what the system can explain, but how it can be evaluated.

Narratives can justify assumptions, but measurement enforces discipline. Calibration, scoring, and live benchmarking turn probability outputs into something the market can continuously audit. With measurement, complexity becomes intelligence.

Yala’s long-term vision is to build fair value intelligence agents for prediction markets: a reliable, accessible probability reference that improves decision quality, reduces information inequity, and enables coordination around verifiable signals.

• Early stage succeeds when probabilities are stable, calibrated, and publicly testable over time.
• Mid stage succeeds when the agent is verifiable in real markets under controlled risk, with measurable performance.
• Late Stage succeeds when multiple agents can be coordinated into coherent cross-domain fair value outputs, and when the system can scale without losing verifiability.

Fair value is the reference point every rational market needs. 

Yala’s mission is to make that reference programmable, empirically testable, and accessible.

Prediction markets are naturally compatible with AI agents, but only if those agents are built for probabilistic reasoning and empirical verifiability through market outcomes.

This article explores how AI changes the structure of prediction markets and why fair value agents represent a new class of market participant.

Prediction Markets Are Fundamentally Probabilistic Systems

Prediction markets are not about narratives alone. They are about probabilities.

A standard prediction market contract pays $1 if an event occurs and $0 if it does not. Its fair value is therefore tied to the probability of resolution under standard assumptions of a $1 payout and negligible frictions.

This makes prediction markets structurally different from most financial markets. They do not price assets with cash flows, growth assumptions, or discount rates. They price uncertainty itself.

As a result, prediction markets systematically reward participants who can:

• Estimate probabilities accurately
• Update beliefs under new information
• Separate signal from noise under uncertainty

What makes prediction markets uniquely agent-native is resolution: outcomes settle, probabilities can be scored, and calibration compounds over time. That turns markets into an evaluation environment, not just a venue for opinions.

The Limitations of Current Forecasting Agents and LLMs

Most AI systems today were not designed for probabilistic markets.

Large language models excel at generating coherent explanations, summarizing narratives. But prediction markets do not reward plausibility. They reward calibration: how often you’re right, by how much you’re wrong when you’re wrong, and whether your probabilities match observed frequencies over time.

General-purpose LLMs are not optimized for calibration by default. Common failure modes include:

• Overconfidence in sparse or ambiguous data regimes
• Sensitivity to narrative framing rather than statistical base rates
• Poor uncertainty presentation
• Inconsistent probability estimates across time

These systems can sound confident without being empirically grounded. In markets with settlement, it’s not just unhelpful, it can be costly.

Forecasting is often “what will happen”. Probability estimation asks: “what is the fair value probability, stated clearly as a percentage and scored against resolution?”

What “AI-Native” Means in a Market Context

An AI-native market agent outputs explicit probabilities that resolve against real outcomes, not just coherent narratives.

In a prediction-market context, “AI-native” means:

• Operating directly in probability space
• Producing testable outputs scored by market settlement
• Updating beliefs continuously as new information arrives
• Being evaluated by empirical outcomes, not narrative coherence

Unlike general LLMs that prioritize plausibility, these agents treat markets as their training environment—where being wrong costs money, and calibration compounds

Probability Estimation vs. Narrative Generation

Narratives turn uncertainty into stories. Probabilities turn it into numbers markets can score.

Human decision-making relies heavily on narrative. Markets do not.

Narrative-driven agents tend to overweight recent events, follow dominant themes, and react sharply to attention dynamics. Probability-driven agents behave differently. They anchor to base rates, update incrementally, and treat new information as a Bayesian adjustment rather than a regime shift.

In prediction markets, narrative generation is a liability. Probability estimation is the core competency.

Verifiability, Calibration, and Feedback Loops

A defining feature of prediction markets is that outcomes resolve.

Every contract eventually settles. Every probability estimate can be scored. Every agent can be evaluated.

This creates an unusually powerful learning environment for AI systems. Prediction markets provide continuous, objective feedback loops that enable:

• Long-term performance tracking
• Calibration analysis and error attribution
• Iterative model refinement based on real outcomes

In prediction markets, empirical verifiability through settlement and scoring is structural.

How Agent-Driven Markets Differ from Human-Driven Ones

As AI agents become active participants, the structure of prediction markets begins to change.

Agent-driven markets exhibit:

• Faster information incorporation
• Quantified narrative impact
• Tighter convergence toward fair value
• Competition on calibration rather than conviction

Mechanically, this happens because agents update continuously, act on smaller mispricings, and operate faster than human attention cycles.

In such markets, alpha does not come from confidence or persuasion. It comes from better probabilistic models and faster adaptation to new information.

Humans do not disappear from these systems, but their role shifts. They increasingly interact with, learn from, and compete against agents whose primary advantage is statistical discipline.

Programmable Probability: The Emerging Market Primitive

Historically, many users have been forced to infer probability from price action.

But as AI-native agents become widespread, probabilities start becoming direct outputs that other systems can consume:

• strategies call them via APIs
• agents compose them across signals and domains
• market participants benchmark against them
• performance is tracked publicly over time

Instead of staring at a contract trading at 0.57 and debating what it means, an agent can publish: 63% fair value, an uncertainty band, and a calibration record. That output can be queried via API, embedded into strategies, and scored automatically when the market resolves.

This is “programmable probability”: probabilities become primitives, auditable, versioned, composable, and continuously scored, rather than subjective impressions.

When that happens, fair value is no longer just a trader’s tool. It becomes a coordination layer.

Yala’s Approach to Building Fair Value AI Agents

Yala builds AI-native agents that output explicit, scorable probabilities as shared market signals: not authoritative predictions.

Instead of asking users to infer probability from price action, Yala makes probabilistic assumptions explicit, measurable, and continuously evaluated in live markets.

Our development arc is staged: 

• Early-stage systems focus on producing stable, interpretable fair value estimates and publishing them publicly, before full autonomous agent deployment.
• Mid-stage agents operate as verifiable market participants, integrating multiple signal sources and validating performance through live trading.
• Late-stage systems expand into multi-agent architectures capable of cross-domain fair value evaluation, subjective pricing, and private-information adjustment.

Across these stages, the emphasis remains constant: probability as a first-class output, calibrated through real-world feedback.

That is the future Yala is building toward.

Prediction markets evolve as probability becomes programmable and agents become native participants.

Prediction markets are frequently framed as the closest thing we have to a real-time consensus engine. People with different information, incentives, and confidence levels trade against one another, and a price emerges that appears to summarize “what the world thinks.”

The story is directionally true, and still incomplete.

A price can be informative without being interpretable. A market can move quickly without offering a disciplined way to judge whether it is moving toward truth or simply drifting with sentiment.

Prediction markets often lack a standardized concept of fair value.

Defining Fair Value in Probabilistic Systems

Markets are good at telling us where the crowd is trading. They are less reliable at telling us what an outcome is worth.

At the simplest level, a prediction market contract is a probabilistic claim. A standard “Yes” contract pays out $1 if an event occurs and $0 if it does not. From a purely mathematical perspective, such a contract has an expected value equal to the probability of the event.

If there is a 60% chance of an event occurring, the fair value is $0.60.

If the market is trading at $0.55, the market is "undervaluing" the outcome.

‘Fair value’ is the price at which a rational participant is indifferent between buying and selling under a specific belief model and risk framework.

Risk-Neutral vs. Subjective Fair Value

In theory, most fair-value reasoning assumes a risk-neutral participant.

Risk-neutral fair value answers a narrow but foundational question:

At what price does this contract have zero expected profit under a no-arbitrage assumption?

Under complete markets, no arbitrage, and risk neutrality, fair value equals expected value. It’s the baseline you expect to break even in the long run.

But real participants are not abstract expected-value calculators. They face constraints:

• Drawdown and tail-risk sensitivity
• Fees, slippage and liquidity frictions
• Settlement ambiguity and rule interpretation risk
• Asymmetric downside around resolution

These constraints introduce a second, equally important concept: 

Subjective fair value is the value of a contract after adjusting probability estimates using contextual, sentiment, macro, and domain-specific signals, as well as uncertainty, risk tolerance, and market frictions.

Both are rational. They compute fair value under different real constraints.

This distinction matters because it clarifies what fair value actually is:

It is probability filtered through a specific risk and information framework, but not probability itself.

Why Market Price Is Not the Same as True Probability 

A common mistake in prediction markets is to treat price as probability without questioning the assumptions behind that equivalence.

If a contract is trading at $0.70, many assume there is a 70% chance of it happening. 

Sometimes this approximation is reasonable. Often, it is not.

Market prices reflect more than just probability. They are shaped by:

• Sentiment: narratives, attention and hype
• Liquidity: thin markets amplify individual trades
• Capital constraints: mispricing can persist if correction is expensive
• Risk preferences: traders may overpay for upside or safety
• Market microstructure: timing, order flow, and short-term imbalances

As a result, the same price can emerge under very different underlying conditions.

Prediction markets tell us where the market is trading. They do not, by themselves, tell us if the market is right.

Without a reference point, participants are left interpreting motion instead of value.

Fair Value as a North Star for Decision Making

In the stock market, investors use "fair value" models to decide if a stock is overpriced. 

Prediction markets generally lack this. Without a standardized reference point, participants are forced to guess based on "vibes" or price action.

Fair value reframes the decision-making process. It moves the conversation away from "Who will win?" toward "Is the current price a statistically reasonable estimate?"

• If Fair Value > Market Price: Buy Signal.
• If Fair Value < Market Price: Sell Signal.

Fair value does not promise correctness on any single outcome. It does not eliminate variance. What it provides is discipline.

It allows participants to evaluate price relative to expectation rather than motion, and functions as a stable reference for navigating uncertainty. 

Why AI Agents Are the Solution

The challenge is that computing fair value is cognitively intractable for humans.

Outcomes in prediction markets depend on many interacting variables: news, sentiment, macro shocks, behavioral feedback loops, and market microstructure. 

Unlike options markets, there is no single closed-form equation that captures these dynamics.

This is where AI agents offer a structural advantage as calibration and signal-integration systems.

Unlike humans, AI agents can:

• Process vast amounts of data instantly to update a probability in real time
• Integrate heterogeneous signals across markets and narratives
• Learn calibration errors over time
• Systematically maintain probabilistic representations where humans are often influenced by narrative reasoning

The goal is to make probabilistic assumptions explicit, measurable and continuously testable.

Yala: Operationalizing Fair Value in Agent Design

Yala aims to build AI-native fair value agents that generate explicit probability signals for prediction markets, signals that serve as shared reference points rather than authoritative forecasts.

Instead of asking users to infer probability from price action, Yala makes probabilistic assumptions explicit, measurable, and continuously evaluated in live markets.

Key design principles include:

• Risk-neutral and subjective fair value separation
• Modular, multi-agent architectures for signal integration
• Continuous calibration through real-market feedback

As Yala evolves from single-agent fair value estimation to multi-agent systems, fair value becomes more than a pricing tool. It becomes a shared language for reasoning under uncertainty.

Prediction markets are often described as some of the most efficient information-pricing systems ever created. By allowing participants to trade on future outcomes, they aggregate dispersed beliefs into prices that represent collective expectations. In theory, these prices should converge toward truth.

In practice, however, prediction markets remain structurally incomplete. Their efficiency breaks down not because of insufficient participation or liquidity, but because they lack a clear and consistent notion of fair value - a benchmark probability against which prices can be rationally evaluated.

This does not mean prediction markets operate without models or external forecasts, but rather that there is no widely adopted, standardized fair-value reference that is native to prediction markets themselves. 

This missing layer becomes increasingly consequential as prediction markets mature into serious financial infrastructure.

Where Prediction Markets Fall Short

Prediction markets excel at aggregating information. They outperform polls in many contexts, update continuously, and incorporate incentives that reward accuracy over opinion. Unlike traditional forecasting mechanisms, they allow beliefs to be expressed quantitatively and refined in real time.

But prices alone do not explain themselves.

A market price reflects more than probability. It also reflects liquidity conditions, risk preferences, capital constraints, leverage, and sentiment. As a result, the same price can emerge under very different underlying assumptions about true likelihood.

Prediction markets tell us where the market is trading. They do not tell us whether the market is right. 

They do not, by themselves, provide a clear reference for evaluating whether that price represents a statistically reasonable estimate of true probability.

The Structural Absence of Fair-Value Benchmarks

In most mature financial markets, fair-value frameworks play an important role. Options markets rely on pricing models, fixed-income markets rely on yield curves, and risk systems use scenario analysis to guide positioning.

These models are themselves uncertain, model-dependent, and often calibrated from market prices rather than independently derived. Their value lies not in precision, but in providing a shared analytical framework for pricing and risk management.

Prediction markets already draw on polls, forecasting models, and expert analysis as external reference points. What they generally lack is a standardized, continuously updated fair-value signal designed specifically for prediction markets and integrated directly into trading decisions.

This absence does not prevent markets from functioning, but it limits their ability to operate as disciplined probability-pricing systems rather than sentiment-driven venues.

Why Sentiment and Price Are Not Substitutes for Probability

Market prices are often mistaken for probabilities. While prices encode information about likelihood, they are shaped by many factors beyond probability itself.

Prices are influenced by:

• who is participating,
• how much capital they control,
• their risk tolerance,
• their time horizon,
• prevailing narratives.

Sentiment can push prices away from statistically grounded estimates, especially in politically charged or event-driven markets. Liquidity constraints can prevent prices from correcting. Short-term narratives can dominate longer-term fundamentals.

Probability, by contrast, is a property of the outcome, not of the market. Without an explicit probabilistic reference point, participants are forced to infer probability indirectly from price action, a process that is inherently noisy and uneven.

Fair Value Reframes Decision-Making

Fair value reframes prediction markets from speculative environments into structured decision systems.

The logic is simple:

• If fair value is higher than the market price, buying “Yes” is statistically favorable.
• If fair value is lower, selling “Yes” is statistically favorable.

Fair value does not guarantee correctness on any single event. Like all models, fair-value estimates are uncertain and dependent on assumptions and inputs. Their value lies in consistency and discipline.

In this way, fair value functions as a north star: not a promise of certainty, but a guide for rational behavior under uncertainty.

Why AI Agents Are Uniquely Suited to This Problem

Estimating fair value in prediction markets is difficult precisely because outcomes depend on many interacting variables. Unlike options pricing, there is no single closed-form equation that captures political dynamics, macro shocks, sentiment shifts, and behavioral feedback loops.

This is where AI-native systems offer a potential advantage.

AI agents can:

• integrate heterogeneous data sources,
• update probabilities dynamically,
• learn from historical outcomes,
• and operate directly in probability space rather than narrative space.

At the same time, AI-generated fair values are not inherently reliable by default; their usefulness depends heavily on model design, data quality, and empirical validation. The opportunity lies in making fair-value estimation measurable, testable, and continuously improvable rather than implicit or ad hoc.

Yala: Fair Value as Market Infrastructure

Yala approaches fair value not as a trading strategy, but as infrastructure.

Its goal is to build AI-native fair-value agents that generate explicit probability signals for prediction markets - signals that can serve as shared reference points rather than authoritative forecasts.

These signals are intended to be evaluated in live markets over time, with performance measured empirically rather than assumed in advance. By making probabilistic assumptions explicit and testable, prediction markets can evolve beyond speculation toward more disciplined information pricing.

As prediction markets increasingly intersect with finance, governance, and global decision-making, fair value becomes less about prediction and more about coordination. 

Today marks the beginning of a new chapter for Yala, a future dedicated to solving prediction markets’ missing piece: a reliable, accessible fair value signal.

Yala’s new AI-native fair value agent is designed to improve predictive accuracy and make advanced probabilistic tools accessible to all users. This roadmap highlights Yala’s evolution into a scalable fair value engine powered by modular AI components and data-driven probability models, ultimately expanding the system’s reach across more markets, domains, and application scenarios.

TL;DR

Yala is evolving into an AI-native fair value agent that provides reliable probability signals for prediction markets worldwide.

Prediction markets are efficient but incomplete, they lack a systematic, high-accuracy fair value reference, creating information inequity and inconsistent pricing. 

Yala introduces a new staged roadmap:

• Early Stage: Closed testing of Yala’s first fair value agent, public release of early fair value outputs on X, establishing Yala’s core fair value methodology.
• Mid Stage: Public launch of the Yala fair value AI agent, with modular architecture, APIs, bot interfaces and fair-value–driven live trading (a prediction-market version of Alpha Arena).
• Late Stage: Expansion into a multi-agent swarm system capable of cross-domain fair value evaluation, subjective pricing, private-information adjustment, and tokenized agent economies.

Yala is building toward a future where fair value AI agents form the probabilistic backbone of global prediction markets, enabling agents, markets, and users to coordinate on accurate, verifiable fair value signals.

The Problem: Prediction Markets Lacks Fair Value Signals

Prediction markets are rapidly becoming one of the world’s most important mechanisms for pricing information. Take the 2024 U.S. presidential election as an example: while major polling agencies showed Trump and Harris in a statistical dead heat, the Polymarket odds strongly favored Trump throughout. As prediction markets mature, few now doubt their ability to surface real-time collective intelligence and price uncertainty more efficiently than traditional systems.

At the regulatory level, this shift has already been recognized. Kalshi’s approval by the Commodity Futures Trading Commission (CFTC) as a Designated Contract Market (DCM) confirms that prediction platforms are no longer treated as gambling venues, they are a distinct class of financial infrastructure. The fundamental reason is simple: their prices are no longer set by bookmakers but determined through order-book matching, where traders negotiate prices that directly represent probabilities.

In many ways, prediction markets resemble options markets. Anyone with experience in derivatives understands the importance of fair value models, such as Black–Scholes, for pricing and risk management. Prediction markets, however, currently lack an equivalent framework. If they are to evolve into serious financial products, a robust fair value model is indispensable.

For individual market participants, the implications are profound. The trader who can more rationally and accurately assess true probabilities is the one who consistently discovers valuable opportunities in the sea of uncertainty. Fair value acts as the “North Star,” guiding users toward statistically favorable decisions.

Yet in practice, calculating fair value is hard. Whether forecasting asset prices, sports outcomes, or political events, results depend on many interacting variables far beyond human cognition. Unlike options, prediction markets cannot rely on a single elegant equation. This is precisely where AI agents show unique advantages: they can integrate complex signals, update dynamically, and output a probability, a fair price for “Yes.”Prediction markets need a fair value intelligence source, and that’s where Yala comes in. 

In practice, the use of fair value is simple and intuitive.

• When the fair value of an event is higher than the market price of “Yes,” a bettor is statistically better off buying Yes or selling No.
• When the fair value is lower than the market price, the opposite is true, selling Yes or buying No becomes the more rational position.

Fair value does not guarantee perfect accuracy, but it consistently improves a user’s decision quality and long-term win rate in probability-based markets. It serves as a north star for navigating uncertainty, turning prediction markets from pure speculation into structured information-pricing systems.

The Yala Roadmap: Building Fair Value, Stage by Stage

Yala’s evolution is grounded in a clear, multi-stage roadmap, each phase deepening intelligence and expanding the design space for what prediction markets and AI agents can become.

Early Stage: Establishing the First Fair Value AI Agent

In the early stage, Yala will focus on releasing a steady and reliable stream of probability estimates across key prediction categories. The Yala AI Agent will be launched in a closed, internal testing phase, allowing rapid iteration ahead of the public launch. During this period, Yala will not only continue advancing the training and refinement of our first fair value AI agent, but will also use the official X account as the primary channel for sharing early fair value outputs.

These initial releases are intended to showcase the direction of Yala’s fair value methodology, how the system approaches calibration, consistency and probabilistic reasoning. As internal development continues, these early signals help lay the foundation for more advanced capabilities that follow in later stages.

Mid Stage: The Public Launch of Yala’s Fair Value AI Agent

As the system matures, Yala moves from private beta to the public launch of its first fair value AI agent, a specialized model designed for price prediction markets and risk-neutral valuation. This phase marks Yala’s transition from publishing raw forecasts to operating a verifiable, measurable agent whose performance is continuously tested in real markets.

At this stage, the agent relies primarily on historical trading data as the foundational signal source for generating risk-neutral fair value estimates, while also incorporating complementary signals such as news-driven event analysis, smart-money tagging information, and social-media-based sentiment dynamics to enhance its contextual awareness and responsiveness.

Users interact with the agent through a simple, structured input format:

• Market type: sports events or crypto markets
• Target condition: target price, direction, or price range
• Time horizon: a specific future timestamp

Based on these inputs, the agent outputs a probability estimate representing the likelihood that the specific condition will be met. This becomes the user’s fair value reference for directional or range-based trading decisions.

In the mid stage, Yala will showcase the agent operating in a small live environment, managing between $1,000–$10,000 in real positions and executing trades autonomously. The goal is to validate the agent’s fair value logic in real markets while maintaining controlled risk limits.

Its architecture adopts a highly modular multi-agent design coordinated by a central Orchestrator Agent. All agents follow a consistent and extensible framework, enabling plug-and-play integration across different prediction-market types and allowing specialized agent modules to be tailored to diverse event scenarios. This modularity ensures rapid adaptation, flexible scaling, and seamless support for new Yala agent components.

• Orchestrator Module: Hosts the Orchestrator Agent, which coordinates all AI agents, manages task routing, merges signals, and ensures coherent end-to-end processing. The Orchestrator also supports plug-and-play integration of different Yala modular agent components, enabling rapid deployment and extension of new agent types.
• Data Ingestion & Processing Module: Includes the Social-Media Processing Agent, News Processing Agent, Historical Market Data Agent, and Smart-Money Analysis Agent, collectively responsible for collecting raw data from Twitter/X, news sources (e.g., Bloomberg), market APIs, and smart-money flows.
• Preprocessing Module: Aggregates, cleans, normalizes, and temporally aligns all multi-source features into a unified model-ready representation.
• Prediction Model Module: Uses an ensemble of LSTM, Transformer, and other time-series models to generate probability forecasts and risk-neutral fair value estimates based on the unified feature space.
• Strategy & Interpretation Module: Includes the Quantitative Strategy Agent, Market Sentiment Agent, and Output Synthesis Agent, turning model outputs and signals into interpretable, strategy-ready insights.
• Safety & Governance Module: Hosts the Safety & Governance Agent, which enforces rules, applies safety constraints, and ensures compliant behavior across all agents and decision flows.
• Monitoring & Deployment Module: Tracks system performance, manages periodic retraining, and exposes the overall system via API endpoints for integration and automation.

This phase also introduces a full suite of backtesting and risk-control systems, as well as strategy-plugin slots for additional trading heuristics and extensions.

During this period, Yala also plans to release MCP-compatible APIs for programmatic fair value queries, alongside lightweight bot interfaces on Telegram and/or X.

Future enhancements may include:

• Options-implied volatility (IV) factors
• On-chain capital flow and liquidity signals
• Bayesian dynamic belief updating
• A calibration engine for probability confidence scoring
• Additional factor-based signals integrated into the fair value model

This transition elevates Yala from simply generating forecasts to delivering a validated fair value agent, one whose outputs are continuously measured, refined, and improved through real-world feedback and live performance data.

Late Stage: The Multi-Agent Fair Value System

In the late stage, Yala will evolve into a comprehensive mutli-agent fair value system capable of evaluating outcomes across markets, signals and event types. The single-agent architecture of the mid stage expands into a coordinated swarm framework in which a Supervisor Agent orchestrates a suite of specialized Worker Agents to generate explainable fair value analysis.

With expanded capabilities, users can provide broader and more flexible inputs: 

• Any asset or event category, spanning the full prediction-market landscape as well as equities, elections, esports, and macro outcomes
• A future time horizon

Based on these inputs, the system generates a complete probability density function (PDF), a multi-factor fair value curve integrating both subjective and risk-neutral probabilities, confidence intervals, and distribution shapes. This provides users with a holistic probabilistic understanding of outcomes, far surpassing a single-point estimate.

Compared with the earlier stages, the advanced agent introduces four major capabilities:

• Beyond risk-neutral pricing: In addition to no-arbitrage fair value, the system will generate subjective fair value estimates that incorporate sentiment, macro factors, and domain-specific context.
• Multi-market scope: Fair value estimation expands from a single price-prediction market into a broad set of domains, including crypto, equities, elections, interest-rate cuts, legislation outcomes, and sports events.
• Multi-factor intelligence: Instead of relying solely on historical trading data, the advanced agent integrates a range of new factors, such as market sentiment, options data, ETF flows, and macro events.
• A multi-agent swarm architecture: The system adopts a layered, collaborative structure in which a Supervisor Agent coordinates a set of specialized Worker Agents.

At the top level, the Supervisor (Orchestrator) Agent coordinates the entire multi-agent system. It parses user queries, assigns tasks to specialized Worker Agents, monitors execution progress, and aggregates all intermediate outputs into final probability and fair value estimates. Under its coordination, the system deploys several Worker Agents, including:

• Fair Value Modeling Agent: Selects and applies the appropriate valuation framework risk-neutral, statistical, or subjective based on event characteristics and available signals.
• Data Collection Agent: Continuously retrieves structured market data across historical and real-time sources, integrating price series, volume, order-flow, and related market features.
• Sentiment Analysis Agent: Processes social-media and news signals, quantifying narrative dynamics and sentiment shifts to generate adjustment factors for valuation models.
• Smart-Money Analysis Agent: Identifies informed trading patterns such as Polymarket front-running behavior and high-conviction smart-money flows, producing directional confidence signals.
• Event Tracking Agent: Detects macro shocks, geopolitical events, regulatory updates, and other catalysts that significantly alter probability paths or regime conditions.
• Options Analysis Agent: Computes implied probabilities and volatility adjustments derived from IV surfaces, skew, open-interest ratios, and other options-market indicators.
• Simulation Agent: Runs Monte Carlo or scenario-based simulations to construct baseline probability distributions and explore alternative market regimes.
• Decision Aggregation Agent: Integrates outputs from all Worker Agents, including model forecasts, sentiment scores, smart-money signals, options metrics, and simulations—into consolidated results such as fair value estimates, probability distributions, confidence intervals, and interpretable explanations.

Together, these agents form a layered, collaborative system for generating rigorous fair value assessments.

The late stage also introduces a trust-minimized, verifiable and community-driven agent environment and the Insider/Private-Information Adjustment Agent, which allows users to securely provide private signals that refine subjective fair values. This agent supports encrypted vector storage and confidential RAG pipelines, offering stronger privacy protections.

Yala will introduce invitation-based or strategy-gated prediction vaults in which advanced agents autonomously allocate capital and take positions on platforms like Polymarket. 

Both the full multi-agent system and individual Worker Agents may be monetized or tokenized:

• via x402 paid agent-access models, and
• through agent tokens that entitle holders to a share of agent-generated revenue

These mechanisms enable a decentralized, economically aligned agent ecosystem.

By this point, Yala functions as a fair value operating system, a coordinated multi-agent environment capable of powering prediction platforms, agent-to-agent economies, and cross-domain forecasting applications. It represents the complete realization of Yala’s vision: a programmable, extensible, and economically aligned system for generating fair value assessments across the uncertainty landscape.

By the end of the late stage, Yala will become a multi-domain fair value AI platform ready for scalable, large-scale commercialization.

Updated YALA Tokenomics

In the next phase of Yala’s AI evolution, the YALA token will become the foundational  governance and value-alignement asset that powers the entire Yala AI ecosystem. By staking YALA, token holders gain the ability to participate directly in the governance of Yala’s multi-agent architecture, including parameter update, agent-level oversight, and platform-wide decision making.

As new protocol modules and revenue-generating products are introduced, a portion of platform income will be allocated to future YALA buybacks. These revenue streams are expected to come from performance fees originating from fund vaults, as well as usage fees generated when users or developers call Yala’s AI agents. As agent adoption increases, these mechanisms are designed to create sustained, long-term value flow back to YALA stakers.

YALA is also positioned to become the central economic anchor for all tokens issued within the agent network. As new tokens emerge, whether from the broader multi-agent system or from individual Worker Agents, YALA stakers will receive distributions and airdrops tied to these expansions. This model ensures that long-term YALA participants capture the upside of the entire agent ecosystem as it grows, diversifies, and launches new tokenized modules.

Looking Forward

A fair value agent transforms prediction markets from betting venues into structured, information-pricing systems. With a trustworthy probabilistic signal, markets can price uncertainty more efficiently, liquidity providers can operate with clarity, and users gain a dependable reference point for navigating complex events. Fair value becomes the shared language that aligns participants, agents, and applications across the prediction economy.

This is the world Yala is building toward: a fair value engine that supports multi-agent coordination, cross-domain forecasting, and. As the system develops, Yala will integrate with a broader ecosystem, agent deployment and tokenization frameworks, MCP-compatible data providers, secure execution environments, and prediction markets that benefit from deeper liquidity and more accurate pricing.

The prediction economy is forming.

Join us as we launch the next chapter of Yala.

Over the past weeks, we have communicated openly with the community regarding liquidity constraints and our commitment to a structured, transparent resolution. Today, we are releasing the full Yala Redemption Plan as promised, including the process, timeline, and how all affected users can participate.

This plan is designed to ensure fairness, clarity and predictable liquidity distribution for all YU participants (including Euler Yala Frontier Vault users), while allowing Yala to continue operating and building through this transition period.

The Redemption: How It Works

At the core of the redemption system is a YU–USDC Redemption Pool, which allows users to deposit eligible assets and withdraw USDC on a 1:1 basis, subject to the monthly available redemption capacity.

Assets Eligible for Redemption

Users may redeem the following deposited assets at a 1:1 rate into USDC (this rate does not include any interest-related amounts):

1. Euler Yala Frontier USDC Vault Token

https://etherscan.io/token/0x481D4909D7ca2eb27c4975f08dCE07DBeF0d3Fa7 

2. YU (Ethereum Mainnet)

https://etherscan.io/token/0xE868084cf08F3c3db11f4B73a95473762d9463f7 

YU tokens on all other chains (Base, Solana etc.) must be bridged back to Ethereum mainnet before they can be redeemed. The buyback/redemption can only be executed in USDC.

Redemption Schedule

From December 15, 2025, at 12:00 PM UTC, the YU–USDC redemption pool will be open for deposits.

Deposit here: https://app.yala.org/redeem

Starting in January 2026, between the 15th and 25th of each month, new USDC capacity will enter the pool. You can decide to claim your USDC the same month or withdraw later in one transaction.

The monthly USDC allocation will be distributed proportionally based on:

• Total YU or vault tokens deposited
• Monthly USDC capacity added to the pool

By December 31, 2026, Yala will complete all YU-USDC redemptions based on the final outcomes of the judicial processes or updated debt assessment following the September 14 incident.

Should any changes arise from these legal proceedings or revised assessments, the team will update the community promptly.

Redemption Guide

The redemption process is simple: deposit your assets, track your claimable USDC in real time, and withdraw whenever you choose. Here’s how it works step-by-step:

Step 1: Deposit

Select the token you want to deposit. If this is your first time, you’ll need to authorize the contract in your wallet.

Deposit YU or Euler USDC Vault Tokens into the Redemption Pool.

Step 2: View Claimable Amount

After depositing, wait for the USDC to be credited. Once the USDC is credited, your redeemable shares will be calculated proportionally, and your token will be bought back.

When new monthly liquidity enters the pool, the interface automatically updates to show your Claimable USDC, calculated based on:

• Available USDC in the pool
• Proportional allocation for the month
• The amount of YU or Vault Tokens you deposited

You can view your balance on the page. Your balance may change each time USDC is credited.

Step 3: Claim/Withdraw USDC

Users may claim or withdraw USDC at any time.

There are no lock-ups and no restrictions on when users can claim.

Please note, users may deposit or withdraw YU and USDC deposit tokens at any time, and may claim USDC at any time.

You can view the Your Deposited YU Balance, Your Euler Vault Token Balance, and Your Claimable USDC directly on the claim page. 

Final Words

To the entire Yala community: Thank you. Your patience, feedback, and support over recent weeks have been invaluable. We understand the frustration and uncertainty this period has caused, and we remain committed to transparency, user protection and long-term responsibility.

Yala continues building. We are moving forward with a new AI-agent roadmap and will share ongoing updates with the community.

If you have questions or need support, please reach out through our official channels:

• Telegram 
• Discord

Thank you again for standing with us.

The Yala Team

Dear Yetis,

After the recent September 14 incident, we sincerely thank our community for their continued trust and patience. 

To reward your support, we are launching the ‘Double Berries’ Loyalty Program.

1. Duration

00.00 UTC September 23rd, 2025 - 09.00 UTC, December 8th, 2025

2. Who Can Join

All users who earned Berries on Yala Mainnet before the end of September 22nd (UTC), will be automatically enrolled in the Loyalty Program.

3. How It Works

• Yala record two types of Berries points: 
  • A = Berries earned on September 22nd
  • C = Total accumulated Berries by 23:59 UTC on September 22nd
• As long as A > 0, then starting from September 23rd till our snapshot at 9am UTC, December 8th, all new Berries you earn will be doubled (2x) based on your existing multipliers. For example, if you were earning 6x Berries, with the bonus it becomes 12x Berries.
  • New Points = hourly points x 2

Pro Tip: 

Keep your positions or add more on September 22nd, 2025 to be eligible for double Berries till the end of Season 2.

4. Notes & Rules

• Make sure your daily Berries earnings remain ≥ 80% of A. If they fall below this level for 3 consecutive days, your eligibility will be canceled.
• If the extra points earned from this program reach 10 times of C:
  • ≤ 10 x C → Still doubled
  • Beyond 10 x C  → normal rate applies.
• The extra Berries points will be added together at the end of each day.

Thank you for standing with Yala! Double Berries is only the start.

This has been the most difficult moment in Yala’s journey. Like many of you, we feel the full weight of this incident: not only as builders but also as members of this community. From the beginning, our deepest concern has not been the financial loss, but how to face the community that placed its trust in us.

We recognize that this event has shaken confidence and take full responsibility for the pain it has caused. Yet despite the depth of this setback, we have chosen to confront it openly, to rebuild stronger, and to remain steadfast in our conviction in Bitcoin and in the vision that gave life to Yala.

TL;DR: Next Tuesday (9/23), $YU will have full liquidity restored and return to its peg.

I. Incident overview

A hacker abused temporary deployment keys during authorized bridge deployment, set up an unauthorized cross-chain bridge, and extracted 7.64M USDC (~1,636 ETH).

• $YU briefly depegged to $0.20 before stabilizing at $0.94.
• No protocol vulnerability was exploited, and no Bitcoin reserves were compromised.

Timeline of events:

• 2025-08-04 14:46:47 UTC — A malicious OFTU token contract was deployed on Polygon by the hacker, establishing the foundational infrastructure for the future exploit.
• 2025-08-12 00:47:22 UTC — During the authorized deployment of Yala’s Solana LayerZero OFT, the hacker secretly exploited a temporary local key to create a peer connection from Solana to the trusted OFTU token contract on the Polygon chain. (Context: temporary single-key deployments were required during the initial phases of the contract upgrade process).
• 2025-09-13 19:20:10 UTC — The hacker activated the 40-day dormant backdoor by configuring the final peer connection from the malicious Polygon OFTU contract to Yala's production $YU LayerZero OFT bridge on Solana, allowing the hacker to bridge malicious tokens from Polygon to Solana disguised as legitimate $YU tokens.
• 2025-09-13 19:44:10 UTC — 120,000,000 OFTU (malicious tokens) were minted in four transactions on Polygon.
• 2025-09-13 20:07:28 UTC — 30,000,000 OFTU were bridged via LayerZero to Solana, resulting in 30,000,000 $YU over-minted on Solana.
• 2025-09-13 20:09:34 UTC — Out of the 30,000,000 in malicious $YU, 10,000,000 $YU were bridged from Solana to Ethereum.
• 2025-09-13 20:11:52 UTC — 2,000,000 $YU were swapped for 1,996,868 USDC on Raydium.
• 2025-09-13 20:25:06 UTC — 1,800,000 USDC were bridged to Ethereum in two transactions via CCTP.
• 2025-09-13 20:25:27 UTC — 500,000 $YU were swapped for 490,697 USDC on Raydium.
• 2025-09-13 20:40:49 UTC — 629,955 USDC were bridged to Ethereum via CCTP.
• 2025-09-13 20:13:35 UTC — 5,213,000 $YU were converted to USDC through the Yala PSM protocol.
• 2025-09-13 20:19:23 UTC — 7,642,852 USDC were swapped for 1,635.572 ETH in four transactions via Uniswap.
• 2025-09-13 20:45:47 UTC — Stolen funds began to be laundered through Tornado Cash.
• 2025-09-16 11:30:17 UTC — Hacker sent over-minted 17,500,000 $YU to Yala Cubist wallet on Solana.
• 2025-09-16 11:37:23 UTC — Hacker sent over-minted 4,787,000 $YU to Yala Cubist wallet on Ethereum.

Hacker addresses:

Current status of funds

Following the unauthorized over-minted of 30,000,000 YU to Solana, the hacker has returned a substantial portion of the assets. The current state is as follows:

1. Total Returned: 22,287,000 $YU

• 17,500,000 $YU on Solana (SOL)
• 4,787,000 $YU on Ethereum (ETH)

2. Remaining converted by the hacker: 7,713,000 $YU to 1,635.572 ETH 

• Mixed via Tornado Cash: 151.5 ETH
• Still held in 146 hacker-controlled, distributed wallets: 1474.6 ETH

II. Immediate response

Following initial notice of events, Yala immediately: 

• Engaged security specialists (SlowMist, Fuzzland) for root cause analysis and impact prevention.
• Disabled the ‘Convert’ and ‘Bridge’ functions to halt further user exposure.
• Contained the exploit to stop unauthorized minting and transfers. Deployed protective safeguards to secure liquidity and preserve systemic integrity.
• Mobilized forensic partners to trace on-chain activity, analyze the exploit, and assess cross-chain/user impact.
• Coordinated with local and international law enforcement after identifying the hacker.

III. Recovery plan

On September 23, 2025 (next Tuesday), all illegally generated $YU will be destroyed, and liquidity will be fully restored: every user will be able to swap $YU for USDC at a 1:1 ratio.

Our core principles in mitigating this incident are as follows:

• Protect all users from any potential losses 
• Burn all the illegally minted $YU
• Audit contracts and bridge settings with internal engineers and external experts (Fuzzland, Cubist)
• Implement extra monitoring for admin actions, bridge status, and contract updates
• Act quickly while maintaining fairness

Breakdown of illegitimate $YU:

1. Polygon (90,000,000 OFTU) – Access to the Yala $YU bridge has been disabled after shutting down the illegal bridge (Polygon)
2. Cross-chained but unused $YU - under Yala’s control and will be burnt on September 23, 2025.

• Ethereum: 4,787,000.1 $YU (Ethereum)
• Solana: 17,500,000.09994 $YU (Solana)

3. Already used by hacker: 7,712,999.80006 $YU

• Yala will repurchase/collect the same amount (via PSM USDC conversions, DEX purchases, and other methods) and burn them on September 23, 2025.

After these steps, all illegitimate $YU will be fully removed from circulation, ensuring that every remaining $YU is valid and backed by sufficient debt or underlying assets. Liquidity will be restored, allowing users to safely exit positions.

Liquidation penalty compensation:

We are aware that some users were unfairly liquidated due to YU’s de-peg and incurred penalties. 

• Starting September 23, 2025, Yala will open a claims process for liquidation penalty compensation. 
• Users should contact Yala staff via Discord to register and confirm their claims. 
• Because each case requires manual review, processing may take 1-4 weeks.

IV. Our commitment

This incident has reinforced a hard truth: trust must never rest on individuals, but on verifiable processes and shared accountability. Building on our existing security infrastructure, including smart contract audits, multisig treasury management, and operational protocols, we are implementing advanced systematic measures that address evolving security challenges. These comprehensive upgrades ensure that no single point of failure can compromise Yala again.

Key action items include:

1. Real-time operational monitoring: We will partner with Fuzzland to implement advanced on-chain monitoring, providing full visibility into all smart contract changes, admin updates, and privileged operations across our protocols
2. Third-party bridge security validation: We have engaged several external security teams as our specialized auditing partner to conduct thorough reviews of all bridge configurations, peer settings, and cross-chain infrastructure. Their audit will confirm no unauthorized connections exist and establish ongoing monitoring for future bridge changes, ensuring full transparency and security
3. Addressing industry limitations: This incident highlighted the evolving nature of cross-chain security requirements, particularly around multisig authorization for complex smart contract operations across different blockchain architectures. We have partnered with Cubist to implement true multi-party control and strengthen governance.
4. Continuous security validation: We perform quarterly security assessments with rotating third-party auditors to ensure fresh perspectives. These reviews go beyond smart contract audits to cover operational security, process compliance, and team practices. Each quarter focuses on different areas, namely infrastructure, operations, strategy, and security culture, creating a continuous improvement cycle.

V. Conclusion

This incident did not arise from the protocol or smart contract exploit. Immediate containment measures were taken, and structural improvements are already underway to prevent recurrence. Yala remains fully committed to protecting user assets, strengthening governance and security, and maintaining transparent communication.

Our priority is to restore confidence in the protocol and the team behind it, safeguard the community’s long-term trust, and ensure Yala emerges stronger and more resilient. We will continue to provide clear updates as forensic investigations and independent audits progress.

The trust you place in us means everything, and we will not stop until every user is made whole. This event has tested us, but it has also reinforced our conviction in Bitcoin and the mission on which Yala was built.

User actions:

• If you did not move your YU/YBTC after the attack, you can redeem directly
• If you did, you will need to submit a claim with transaction details
• Official redemption and claim instructions will follow across social media and website. Stay tuned. 

Welcome to Yala - your bridge between Bitcoin and the world of DeFi yields. 

The process is simple: Mint $YU - the Yala Bitcoin-backed stablecoin - and put it to work. If you’ve already minted $YU, you’re well on your way. If not, start here to earn real yield and stack Berries. 

This guide will walk you through the key ways to earn DeFi yields with $YU on Yala mainnet.

Overview: Earning with Yala

Let’s walk through each of these step-by-step.

1. Stability Pool

Secure the Yala protocol and earn yield in return.

When you stake your $YU in the Stability Pool, your $YU is used to absorb liquidated debt. In exchange, you receive liquidation gains in YBTC and bonus $YU rewards. In many cases, these rewards can offset or even exceed your original stake.

How to stake in the Yala Stability Pool:

• Go to Earn → Stability Pool
• Enter amount of $YU to stake
• Click 'Stake' and confirm in your wallet

Note: Make sure you have $YU in your wallet. If not, you can Convert from USDC with no slippage or Buy $YU from a DEX.

2. Yield Farming

Fuel the Yala ecosystem and earn rewards. Provide liquidity for supported pairs (like YU/USDC or YBTC/WBTC) on Uniswap V3 to earn swap fees and stack Berries as bonus rewards.

Start farming in 3 steps:

1. Step 1 – Choose a Pool

• Go to Earn → Farming
• Choose from available pools (e.g. YU/USDC, YU/WBTC)
• Click "Provide Liquidity."

Step 2 – Add Liquidity on Uniswap V3

• Make sure you’re on Uniswap V3, using the 0.01% fee tier
• Set a price range between 0.99 – 1.01
• Enter the amount of one asset – Uniswap will auto-calculate the other
• Approve spending and confirm the transaction in your wallet
• Once added, your LP position will appear on Uniswap as an NFT token

Step 3 – Stake Your NFT Tokens on Yala 

• Return to the Farming on Yala
• Click “Stake NFT Tokens”
• Choose the position you want to stake → click "Stake." 
• Approve and confirm the transaction in your wallet

Reminder:

• If you only hold NFT Tokens, you’ll earn swap fees.
• If you stake them on Yala, you’ll earn swap fees + Berries (Yala ecosystem & airdrop points.

3. Deposit with Lite Mode

Put your $YU to work effortlessly.

Deposit your $YU or USDC into Lite Mode and earn 2x-5x Berries plus up to 20% fixed APR. All managed securely in the Yala Vault.

How to deposit:

1. Go to yala.org → select “Lite Mode" and connect your wallet.
2. Click “Prime Invest” → enter the amount you want to deposit.
3. Confirm the transaction in your wallet.

4. Explore the DeFi Marketplace

Looking for more ways to earn? The Yala DeFi Marketplace lets you deploy $YU across multiple chains and top protocols, unlocking yields and 3x-6x Berries all in one hub.

To Get Started in the DeFi Marketplace

• Visit the DeFi Marketplace: app.yala.org/defi-marketplace.
• Select a protocol you want to interact with (e.g., Pendle, Kamino, Raydium, RateX, Penpie, Equilibria, Euler and/or NX Finance).
• Review the mission and rewards (APR, Berries multiplier, extra incentives).
• Click “Go” next to your chosen protocol.
• Connect your wallet and follow the instructions (buy, stake, or provide liquidity).
• Confirm the transaction in your wallet.

For step-by-step tutorials on each protocol, visit here.

5. Earn RWA Yields with Yala RealYield

Access real-world yield from a range of public and private credit strategies, earning 4 – 9.3% APR through platforms like BUIDL (BlackRock) and JTRSY (Centrifuge) for public credit backed by U.S. Treasuries, and ACRED (Apollo Securitize Fund) for private credit exposure.

Bookmark this blog. More ways to earn with Yala are on the way.

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs

August wasn't just another month for Yala—it was the month everything clicked. With $219 million TVL, 1,870 Bitcoin holders embracing yield opportunities, and the Base integration unlocking a whole new chapter, we’re moving from ideas into real, unstoppable momentum.

What started as “let’s see what’s possible with Bitcoin yield” is now becoming the standard. Across Solana, Base, Ethereum and beyond, Yala is building the rails for anyone, from retail to institutions, to put BTC to work safely and simply.

Quick August recap:

• $219M TVL & $133M YU minted → Just 3 months in, Bitcoin holders are voting with their wallets.
• Base integration live → $YU & $YALA now supported with seamless bridging + new Pendle pool.
• Pendle ecosystem mastery → Dual integrations (Penpie + Equilibria) boosting yields & simplifying governance.
• NX Finance on Solana → $YU supply & leverage strategies with extra Berries rewards.
• Community vibes → First Yetis Talk live call, Yield Madness Spaces with Pendle, and trading competitions via Aerodrome & PancakeSwap.
• Rewards unlocked → 40k $YU incentives on Kamino, 20k $YU on Euler, $7k voting rewards, and auto Berries for $YALA holders.

If you only remember three things: Base went live, Pendle integration got real, and the community is on fire.

Ecosystem and Adoption Expansion

The market appetite is undeniable. Three months in, Yala has:

• $219 million TVL
• $133.11 million in $YU
• 1,870 BTC minted

A clear proof that adoption is accelerating, with retail and institutional confidence rising across DeFi and real-world assets.

Base Integration: A Strategic Milestone

Successful Base Deployment 

August marked a major expansion for Yala with our Base integration. Both $YALA and $YU are now fully supported on Base, unlocking enhanced utility and smoother user experiences.

Bridge Integration 

We've made cross-chain yield simpler than ever with Stargate Finance integration and Yala’s own bridge tool:

• $YALA: Seamless bridging across Ethereum ↔ Base ↔ BNB Chain
• $YU: Complete liquidity flow between Ethereum ↔ Solana ↔ Base

This upgrade removes friction for users who want to optimize yields, while keeping the security and simplicity Yala is known for. With Base as the gateway, accessibility is no longer a barrier.

Enhanced Infrastructure on Base

As an open, permissionless Ethereum L2 incubated at Coinbase, Base is a critical gateway for mainstream adoption. By expanding to Base, Yala is positioned to capture growing institutional and retail demand flowing through this high-performance, low-cost infrastructure.

Key features include:

• Zero-slippage USDC ↔ $YU conversions on Base
• Seamless Ethereum ↔ Base bridging for $YU

• Dedicated Pendle Pool on Base, supporting advanced yield strategies and giving BTC-backed users new ways to diversify and optimize returns

DeFi Marketplace Expansion

Pendle Ecosystem Mastery

Penpie Integration seamlessly connects $YU with Pendle's yield optimization ecosystem. Holders can stake LP-YU tokens on Penpie to unlock boosted returns, without the hassle of vePENDLE locks or governance management. Penpie handles voting power aggregation and redirects emissions to maximize yields for $YU liquidity providers, while layering in extra Berries rewards.

On top of Penpie, we also integrated Equilibria, completing a dual-integration strategy that gives $YU holders access to liquid vePENDLE power via ePENDLE tokens. With both options in place $YU users now have multiple pathways to optimize Pendle yields, further cementing $YU as a premier asset within the broader Pendle ecosystem.

Solana-Native Lending with NX Finance

We’re extending lending utility to Solana with NX Finance, ensuring $YU delivers consistent lending functionality across major blockchain ecosystems. 

With NX Finance, you can:

• Supply $YU to earn yields
• Leverage $YU to borrow more $YU
• Earn 3x/6x boosted Berries rewards along the way

As Solana's composable yield layer, NX Finance is built for users seeking to earn, leverage, and maximize rewards without complicated DeFi gymnastics.

Explosive Growth & Market Recognition

On Aug 19, Success Cap 4 ($15M) opened and quickly filled, bringing the total $YU cap to $125 million, a clear sign of continued institutional and retail confidence in Bitcoin-backed stablecoin infrastructure.

Lite Mode Phase 3 launched with $1 million capacity at 20% fixed APR, with 2× multiplied Berries, and sold out instantly, proving once again that simple, high-yield BTC products are in massive demand.

Protocol Developments

Building the infrastructure of tomorrow required precision, innovation, and seamless execution across multiple chains. In August, Yala delivered on all fronts, advancing key technical milestones that strengthen our foundation.

Cross-Chain & Liquidity Infrastructure

Wallet Integration Enhancement  

Our multi-chain wallet, which already supported EVM and Bitcoin connections, now includes Solana support.

This enhancement allows seamless asset management across Base, Solana, Ethereum, BNB Chain and Bitcoin networks, creating a unified cross-chain experience.

Real-Time Berries & Ice Berries Tracking 

Real-time tracking for Berries and Ice Berries is now available across Base, Solana,  Ethereum and BNB Chain networks, with independent leaderboards for Base and Solana users. This not only adds transparency but also sparks fresh competition across our multi-chain rewards ecosystem.

Solana Native Protocols 

Development continued on Yala’s native minting protocol for Solana, enabling direct BTC bridging from the Bitcoin network into Solana. 

In parallel, frontend development for Solana’s native lending protocol progressed, while associated smart contracts were finalized and prepared for auditing. 

These efforts push Yala closer to unlocking seamless BTC liquidity and decentralized lending within Solana's high-speed, low-fee environment.

Global PSM Development 

We kicked off development of the Global Protocol Stability Mechanism (PSM), designed to enable flexible liquidity allocation across multiple chains. This system will ensure robust coverage, optimize capital deployment, and reinforce Yala's infrastructure for multi-chain yield strategies.

Product & Adoption

Token Airdrop 

The Season 1 token airdrop was successfully completed, ensuring fair and transparent distribution to early supporters while strengthening community engagement.

Transparency Hub Upgrade

The updated Yala Transparency Hub is now live, providing real-time tracking of key metrics including TVL, Collateralization Ratio, USDC reserves, and $YU circulation. Open-source infrastructure, audits, and multi-chain support are fully accessible, offering enhanced visibility and trust across the ecosystem.

Yay-Agent: AI-Powered Yield Guidance 

Meet Yay-Agent, your personal AI scout for optimal yield opportunities on Base. Yay-Agent delivers tailored recommendations, live stats from top Base protocols, and risk-adjusted strategies, all designed to help users identify and capture optimal yield opportunities.

Community Momentum

Community engagement leveled up in August. From live calls to industry dialogues and reward-driven programs, we’re building deeper connections and ensuring every voice in the Yala ecosystem is heard.

Yetis Talk: Episode 0

We launched Yetis Talk, Yala’s first-ever live voice call series, creating a direct two-way dialogue with our community.

• Users can ask questions, share ideas, and give feedback in real time
• Our team shares key updates and roadmaps directly
• The format lays the groundwork for future DAO governance, where community voice directly shapes protocol direction

Yala Yield Madness #01 – Pendle

We launched our new industry dialogue series, "Yield Madness", with Pendle Finance featured in our first episode. This series creates a long-term channel for engaging with diverse industry leaders and protocol innovators, sparking ongoing conversations that drive the DeFi ecosystem forward through collaborative insights and strategic partnerships.

PankeSwap AMA

Alongside Yetis Talk and the launch of Yield Madness, Yala also joined PancakeSwap’s AMA on Aug 20 to discuss Bitcoin’s untapped yield and how it can power the future of DeFi and RWAs. This AMA opened a fresh channel to connect with the broader DeFi community, expand awareness, and spark dialogue around Yala’s role in shaping yield across ecosystems.

Incentives & Rewards

At Yala, we believe success is something to be shared. Our rewards go far beyond standard DeFi yields, they’re designed to empower, engage and recognize our community members building alongside us.

Automatic Berry Rewards 

All $YALA holders now earn automatic Berries (no staking or claiming):

• Base Berry rate: 0.05 Berries/hour
• $YALA holders on Ethereum, BNB Chain, or Base: 0.5 Berries/USD/hour (10× base rate)

Governance & Voting Incentives 

We reward users for active participation in governance and yield optimization:

• $7,000 USDC incentives in the Penpie Voting Market, offering +50% APR for vlPNP voters supporting $YU pools.
• 3,000 USDC in rewards for YU boosted pool voting.
• 40,000 $YU rewards for YU-USDC LPs on Kamino Finance, and 10.70% APR.
• 20,000 $YU rewards on Yala–Euler, boosting APRs up to 20.7%, renewed monthly.

Trading Competitions 

Yala brings rewards to traders across platforms:

• Aerodrome: 200,000 $YALA prize pool for top 1,805 traders (August 20–30)
• PancakeSwap: $50,000 rewards pool for traders with $2,000+ volume (August 7–31)

Yeti Footprints & Community Engagement

In August, Yeti Footprints kept Bitcoin culture front and center.

• Yeti Yell (Phase 1) rewarded authentic voices, praise, critique, or questions, over empty noise.
• Yeti Lens (Phase 2) empowered creators to turn real knowledge into sharp, digestible visuals.
• Yeti Echo (Phase 3) amplified memes and cultural alpha that spread faster than code.

Together, these phases laid a culture-first foundation for Yala’s ecosystem. And with the Season 2 Airdrop snapshot on October 8th, we’ll continue rewarding those who shape, question, and celebrate BTC and Yala.

What's Next

September is all about refining what we’ve built, perfecting the Base integration, shipping Solana lending, and finalizing the Global PSM to make Bitcoin yield as seamless as opening a bank app. 

We’re also laying the groundwork for Yeti Card partnerships and RWA products, expanding Bitcoin yield across DeFi and RWAs.

Our mission is simple: make Bitcoin yield safe, simple and accessible, for institutions, builders and everyday holders alike.

👉 Join us, earn with us, and let’s define the Bitcoin yield standard together.

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs

​​Looking to tap into high-speed yield opportunities with partners like RateX and Kamino via the Yala DeFi Marketplace? Or aiming to join a campaign with a 10x Berry multiplier on Base? Or maybe you just want to explore on chains with lower gas fees？

First you’ll need to move your $YU and $YALA from Ethereum to other chains such as BNB Chain and Base.

In this guide, we’ll walk you through two ways to bridge:

• Using the Yala Bridge Tool, directly in-app
• Using Stargate for cross-chain transfers

Before You Start

Make sure you have:

• $YU/$YALA on the source chain
• A wallet for the source chain (e.g., MetaMask)
• A destination chain wallet (e.g., Phantom, OKX Wallet)
• The native token of the source chain for gas + a small LayerZero bridge fee (if using the Yala Bridge Tool)

Supported routes:

• $YALA: Ethereum ↔ Base ↔ BNB Chain
• $YU: Ethereum ↔ Solana ↔ Base

Option 1: Bridge with the Yala Bridge Tool

The Yala Bridge Tool, powered by LayerZero, provides a seamless and secure way to transfer your $YU and  $YALA  across chains.

How to Bridge:

• Connect your wallets for both chains.
• From the Yala Mainnet interface, navigate to the "Portfolio"  and click “Bridge.”
• Enter the amount of the asset you want to transfer (i.e., $YU and $YALA) and select your target chain (e.g., Solana or Base).
• Approve the transaction in your wallet.

Track the status of your transfer anytime in the ‘Bridge History’ section at the bottom of the tool.

Note: Double check the amount. Once you confirm, the transaction is irreversible.

Option 2: Bridge with Stargate

Stargate is a composable cross-chain liquidity transport protocol that enables seamless asset transfers across blockchains. You can search for $YU or $YALA directly on Stargate and start bridging.

How to Bridge:

• Go to https://stargate.finance/  and connect your wallets on both chains. 
• Click “Transfer” and select $YU/$YALA (Ethereum) in the From section, and then choose $YU/$YALA on your target chain (Solana, Base, or BNB Chain) in the To section 
• Enter the amount you want to bridge and click “Transfer.” 

Confirm the transaction in your wallet.

What’s Next?

Now that your $YU and $YALA are on the target chains, it is time to put them to work where the yield or Berry rewards are.

👉 Start bridging your assets today!

Once bridged, you can move freely across Ethereum, Solana, Base, and BNB Chain. You may choose the Yala DeFi Marketplace to start earning and stacking Berries, join a trading competition on Base, or simply complete a holding quest. 

The choice is yours.

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs

Alongside Euler, the Yala DeFi Marketplace has onboarded another leading protocol to expand its Money Market to bring users more yield opportunities on Solana.

With NX Finance, $YU holders can supply $YU to earn interest or leverage your $YU to borrow more $YU, all while stacking boosted Solana Berries.

What is NX Finance?

NX Finance is a Solana-native DeFi protocol that leverages Solana’s low fees and high-speed network to offer lending, leveraged trading, and liquidity provision, backed by built-in risk controls and reward mechanisms.

Unlike single-purpose lending or farming platforms, NX Finance integrates multiple strategies to meet different risk profiles, including GMS (General Margin Strategy) and Delta Neutra Strategy. For example, with GMS you can use collateral to borrow assets, which are then auto-deployed into external strategies – such as borrowing $YU and having it automatically deployed into RateX to earn real yield.

On top of these strategies, NX Finance provides multiple layers of rewards, such as Berries in addition to the base yield, giving users the opportunity to boost overall returns.

In short: NX Finance opens the door for $YU holders to access diverse Solana-based yield strategies, enabling your assets to generate steady returns across different risk profiles.

What can you do with your $YU?

With NX integrated into Yala’s DeFi Marketplace, $YU holders can unlock boosted Berries through supply and leverage strategies. Here’s how each option works:

Note: The higher your leverage, the higher your borrowing rate. If the $YU supply in the pool is tight, rates will climb even further – just like taking a taxi: when cars are scarce, prices surge, and the farther you go, the more you pay.

1. Use $YU as Collateral to Borrow more $YU → 6× Berries/hour on borrowed amount

• In Yala mainnet, open the DeFi Marketplace tab.
• Select NX Finance and click Go.
• Enter the $YU amount to deposit as collateral, choose your leverage level, and click Add.
• Confirm the transaction in your wallet.

NX will automatically deposit the leveraged amount into RateX as an LP token, allowing you to earn more Berries compared to using no leverage.

2. Supply $YU to the NX lending pool → 3x Berries/hour

• Go to the lend page.
• Find the $YU pool, click Deposit and enter the amount.
• Confirm the transaction in your wallet.

More Yield Opportunities on Yala

From our first Money Market integration with Euler to the newly launched NX Finance, Yala now gives users the keys to top-tier protocols on both Ethereum and Solana – unlocking real yield across multiple ecosystems.

We’ve also brought $YU to Base, delivering Bitcoin-backed liquidity to one of DeFi’s fastest-growing networks. Base offers a gateway to compliant, accessible DeFi, while letting you earn boosted Berries along the way.

Together, these milestones send a clear message to the industry: Yala is fast becoming the go-to hub for flexible, high-yield DeFi opportunities.

→ Bridge to Base

→ Catch up on past guides

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs

GM Yetis!

Yala is excited to launch its first trading competition on Base!

To celebrate our Base expansion and reward our most active community members, we are giving away 200,000 YALA to the top 1,805 traders who help drive $YALA liquidity and volume.

Promotion Period: August 20, 2025 – August 30, 2025

Total Prize Pool: 200,000 $YALA

How to Participate

• Trade YALA/USDC (Base) on Aerodrome. Both buys and sells count toward your volume.
• Be ranked among the top 1,805 unique wallet addresses by $YALA trading volume.
• Hold at least 1 $YALA in your wallet at the end of the event.

Simple. Earn while you trade!

Reward Tiers

• Special Tiers (Top 5): 5,000 $YALA each (25,000 total)
• Tier 1 (Ranking 6-105): 600 $YALA each (60,000 total)
• Tier 2 (Ranking 106-305): 200 $YALA each (40,000 total)
• Tier 3 (Ranking 306-1805): 50 $YALA each (75,000 total)

Important Notes

• Only on-chain trades in the YALA/USDC (Base) pool on Aerodrome are eligible.
• Each wallet address can only win once. Multiple entries will be filtered.
• Rewards will be distributed to the eligible addresses within 7 working days after the campaign ends.
• Suspicious activity or wash trading will be disqualified.

Start trading today and claim your share of 200,000 $YALA!

Start trading: https://aerodrome.finance/swap?from=0x833589fcd6edb6e08f4c7c32d4f71b54bda02913&to=0xf970706063b7853877f39515c96932d49d5ac9cd&chain0=8453&chain1=8453

All it takes is a simple trade.

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs

Euler is now live on the Yala DeFi Marketplace, expanding Yala’s footprint across Ethereum’s DeFi ecosystem.

With this integration, $YU holders can supply USDC or $YU on Ethereum to earn lending yields and access leverage through Euler’s capital-efficient infrastructure, while also earning boosted Berry rewards from Yala.

What Is Euler?

Euler is an innovative modular lending protocol on Ethereum that lets anyone create isolated and permissionless lending markets for almost any ERC-20 token.

It maximizes capital efficiency and minimizes risk with features like dynamic interest rates, MEV-resistant Dutch auctions, and isolated vaults that shield users from unrelated bad debt.

For users, Euler offers a secure and flexible platform to lend and borrow crypto assets without governance delays – all while enjoying enhanced safety and composability.

Euler unlocks lending yields through three core mechanisms:

• Interest from borrowers
• Liquidity mining and protocol rewards
• Advanced strategies

In short: Euler turns idle crypto into productive assets with high capital efficiency and multiple earning options.

What Can You Do with Your $YU on Euler?

With Euler now integrated into Yala’s DeFi Marketplace, $YU holders can unlock boosted Berries through supply and leverage strategies. Here’s how each option works:

Note: Staking PT-YU itself does not earn Berries rewards

Head over to the DeFi Marketplace tab in the Yala mainnet and get started in seconds.

Supply USDC for lending

• Go to the DeFi Marketplace tab in the Yala app and click "Go"
• Select the USDC row, then click "Accept Terms of Use"
• Enter the amount to supply and click "Supply"
• Confirm the transaction in your wallet to start earning interest.

Supply $YU for lending

• Select the YU row and click "Accept Terms of Use"
• Enter the amount of $YU to supply, then click "Supply"

Use PT-YU as Collateral to Borrow

• Navigate to the "Borrow" page within Euler and select the PT-YU market, and click "Accept Terms of Use"
• Supply PT-YU as collateral, enter the amount of $YU to borrow, and click "Open Position"
• Confirm the transaction in your wallet to proceed.

Note: You’ll need to purchase PT-YU on Pendle before using it as collateral. Not sure how? Here’s a guide.

Earn with Yala

The Yala DeFi Marketplace has launched its first Money Market integration with Euler, enabling users to lend assets like USDC, ETH, and $YU or borrow against them on Ethereum.

This builds on earlier integrations with Penpie, Equilibria, Raydium, and Kamino, which have already broadened Yala’s coverage across yield boosting and LP strategies.

Meanwhile, with $YALA live and Lite Mode yields underway, Yala is shaping up to be a go-to hub for flexible, high-yield DeFi opportunities.

→ Explore Lite Mode

→ Catch up on past guides

Join the Yala Community

Yala is a native Bitcoin liquidity protocol that channels BTC into yield opportunities across DeFi and RWAs. 

Bitcoin holders unlock capital through self-custodial, liquidation-free borrowing by minting $YU, a BTC-backed liquidity asset. In this process, they pay a stability fee directly to $YU depositors, effectively exchanging BTC-backed exposure for portable, capital-efficient liquidity and access to yield without giving up ownership.

Yala’s SmartVault module manages system risk and ensures efficient yield distribution.

Website | Twitter | Telegram | Discord | Docs