The end of AI is not to create the strongest model, but to mobilize an entire network of models for collaborative decision-making.

Allora is doing just that.

This project began building in 2019, raising $35 million, backed by well-established VCs like Polychain, Framework, and Delphi Digital. The core team comes from Chainlink, Coinbase, and LayerZero, making it very solid.

Its core concept is simple – instead of building models, it coordinates hundreds of thousands of models to 'meet and reason' together to provide smarter answers.

The official name is 'Model Coordination Network', but I think of it as the brain of AI Agents, or the Chainlink of the AI world, aggregating dispersed models together and then calling them uniformly.

Currently, Allora's test network has already run nearly 700 million smart inferences, calling upon 280,000 models, with real-world applications, such as predicting the U.S. election, and it has made a 67.65% annualized return on the Polymarket.

The underlying logic is: shifting from a model-oriented approach to a goal-oriented one. You don’t need to worry about which model is the most suitable; you just need to tell Allora what problem you want to solve, and it will dynamically call the most appropriate model combination to address it.

As AI continues to increase, so do illusions and risks. Rather than trusting a single model, it is better to trust the consensus of an entire network of models.

Allora's TGE is coming soon, and this solution provides a new direction for AI, where collaborative decision-making may become a part of future infrastructure.