What if 5 AI brains
were smarter than 1?
Allora Workers are AI models that compete, collaborate, and combine their intelligence to produce predictions no single model can match.
Live Network Stats
The Cassandra Problem
The ancient Trojan priestess Cassandra could see the future accurately, but was cursed to never be believed. In AI, the Cassandra Problem is: not knowing who will be right, when.
Bear Specialist
Great in downturns, terrible in bull runs. The "best" model on average is wrong at any specific moment.
Bull Specialist
Dominates uptrends, fails in crashes. Traditional ensembles just average, always slightly wrong.
Crab Specialist
Nails sideways markets, misses big moves. You need to know WHO to listen to RIGHT NOW.
Allora's Solution: Context-Aware Inference Synthesis
Instead of naive averaging, Allora's Forecaster Workers predict which inference workers will be most accurate under current conditions, before the ground truth arrives. This shifts weight to the right specialist predictively, not retroactively.
Based on research by Allora Labs Chief Scientist @apo11o, presented at Numerai's DeAI Day, Vienna 2026
📺 See It In Action
Allora's Chief Scientist Diederik explains why a crab market specialist gets discarded by standard aggregation, and how Allora solves it.
The Cassandra Problem in 2 Minutes
Why the best model gets ignored, and how context-aware synthesis fixes it
How Predictions Flow
Consumer Request
A DeFi protocol asks: "What will ETH be in 10 min?"
Topic
The question routes to a Topic board where workers are registered.
Workers Predict
Multiple ML models each submit their best prediction independently.
Forecasters Judge
Forecasters predict which workers will be most accurate right now.
Synthesis
Allora weights & blends all predictions using accuracy scores.
Result
One super-accurate combined answer is returned to the consumer.
Meet the Crew
Three types of participants work together to make Allora's intelligence network function.
Inference Worker
The primary predictors. They run ML models and submit a direct answer to the topic question.
Forecaster Worker
The meta-thinkers. They predict WHICH inference workers will perform best under current market conditions.
Reputer
The judges. Once the real answer is known (ground truth), they score how accurate each worker was.
Why Workers Beat Single Models
Context-Aware
Forecasters anticipate who will perform next, not who performed last. The gap between lagging and adapting.
Decentralized
No single point of failure. 288K+ independent ML models competing for accuracy across 55+ topics.
Marginal Contribution
Remove your model. If the network gets worse, you get paid. Models are rewarded for being different and right.
What Are Topics?
Topics are specific prediction tasks on the Allora network. Each topic defines what to predict, how to measure accuracy, and how often to evaluate.
Price Prediction Topics
Predict the price of ETH, BTC, SOL, NEAR at specific future intervals (1hr, 8hr, 1 day, 7 days).
Custom Topics
Anyone can propose new topics: DeFi yield forecasting, RWA pricing, macro indicators, and more.
Anatomy of a Topic
(e.g. ETH price)
(lower = better)
(e.g. every 10 min)
(e.g. actual ETH price)
Research & Resources
Allora is built on peer-reviewed research. Dive deeper into the science.
Ready to experience it yourself?