Allora L1 / L2 Ecosystem

July 23, 2026

If you run or build on an L1 or L2 today, you are competing for the same scarce thing: builders who will ship something people actually use. And increasingly those builders want to ship AI-native apps, agents that trade, vaults that reprice risk, markets that resolve on a forecast. The problem is that a blockchain gives them execution and settlement, not intelligence. There is no native place on-chain to get a reliable, forward-looking prediction. So every AI app has to source its own models, run its own inference pipeline, and maintain it as the market moves. The intelligence is the hard part, and the chain hands you none of it.

Allora is the leading Model Coordination Network (MCN): a decentralized AI network that coordinates many specialized machine-learning models around a shared objective, weighting them in real time and aggregating their output into a single forecast that consistently beats any one model on its own. It produces forward-looking inference, price forecasts, volatility, probabilities, risk, that apps and agents consume via API or on-chain.

In most segments Allora's forecast informs a decision. In the L1 / L2 segment it is used as infrastructure: a composable intelligence layer that a chain switches on so every builder on it can call a forecast without leaving the chain.

Allora's intelligence already reaches across some of the leading names in the space. Confirmed chain and composable-layer integrations include NEAR, TRON, Mantle, Monad, and Story Protocol, with a wider set of L1s and L2s that map cleanly onto the same pattern.

Where Allora Powers What Builders Ship

Mantle. Mantle is a high-performance modular Ethereum L2. Its integration with Allora brings the network's aggregated AI models to Mantle developers directly, so a lending protocol can pull real-time risk models for dynamic loan-to-value ratios and liquidation factors, and any app can source price feeds for long-tail and illiquid assets that standard oracles do not cover. The forecast becomes a primitive Mantle builders call, not a pipeline they build.

TRON. Allora's predictive intelligence is live on TRON, putting the network's forecasts in reach of one of the largest stablecoin and payments ecosystems in crypto. Builders on TRON can consume price and risk inference to drive on-chain logic rather than importing signals from off-chain services.

Monad. Monad is a high-performance, EVM-compatible L1. Allora brings predictive feeds to Monad so EVM developers can plug intelligence oracles straight into smart contracts, powering autonomous agents that execute trading and hedging, indexes that adjust exposure, and prediction markets that resolve on collective-intelligence forecasts.

Story Protocol. Story is a purpose-built L1 that tokenizes intellectual property into programmable assets. Its Allora integration merges AI with IP: the network can generate real-time price feeds for IP assets through techniques like upsampling, and Story protocols can use Allora's aggregated risk models and forecasts for price, volatility, liquidity, and interest rates to power yield strategies and adaptive fee structures on IP-backed markets.

NEAR. NEAR is a high-throughput L1 with a strong focus on AI and abstraction. As a confirmed integration, it extends the same pattern: Allora's forecasts become available to NEAR builders as a callable layer rather than something each app assembles alone.

Beyond the confirmed set, the map includes chains that fit this pattern precisely and are worth watching. Hemi is a modular L2 that gives contracts awareness of Bitcoin state, the kind of BTCFi surface where risk and price inference on long-tail collateral would matter. Plume is an L1 built for real-world asset finance, where forecasts on illiquid RWAs are exactly the gap Allora fills. Soneium (Sony's Optimism-based L2), Sonic, Berachain, Cronos, Mode, Eclipse, zkSync, Omni, Duckchain, Novastro, and Zypher Network each run AI-driven or DeFi-heavy app surfaces that a composable intelligence layer could serve.

What Allora gives an L1 / L2 builder

The builder's real problem is not execution. It is the edge. Sourcing good models, keeping them accurate, and fighting decay as the market shifts is a full-time machine-learning job most app teams cannot staff. That work sits between them and shipping.

Allora hands them the output without the overhead. A team calls a forecast, price, volatility, a probability, a risk metric, the same way they call any other on-chain read, and the coordination, weighting, and continuous retraining happen inside the network. No pipeline to maintain, no models to babysit.

Because Allora deploys as a neutral, composable layer rather than a walled service, a chain can offer this to every builder on it at once, and no builder is locked in. Each new chain and app that plugs in adds demand that sharpens the models, and the intelligence gets better for everyone already connected.