Quantitative research platform for Hyperliquid.
Algosia trains, compares, and deploys AI models on Hyperliquid order books and trade history. The platform activates terabytes of data on demand, covers more than 100 coins, and produces predictions over tens of seconds or minutes.
Market data turned into testable signals.
The platform works on highly granular data to capture market microstructure, validates models through robust backtests, and keeps only signals that can realistically support trading decisions.
A broad Hyperliquid research universe.
More than 100 coins can be used to train, compare, and test models without changing the research engine.
Data & statistics
Inspect distributions before training.
The platform builds coin and horizon windows, launches statistics jobs, and exposes log-return distributions so targets are framed before heavy ML campaigns.
Machine learning
Track training and features in real time.
Jobs materialize features, prepare targets, and stream LightGBM curves during execution so train/valid quality remains visible inside the workspace.
Infrastructure
Use local or cloud compute without changing interface.
The same dashboard drives jobs locally or on Vast.ai capacity, surfaces CPU/RAM, and returns model metrics, validation distributions, and feature importance.
Backtests & live
Validate signals before connecting them to live.
Strategies are checked through PnL, win rate, confusion matrices, and prediction distributions before they feed autonomous loops and live trading.