Stratify is the end-to-end platform for AI-driven trading intelligence. Our Large Multi-Modal Model fuses time-series data and financial text to deliver institutional-grade execution.
A product built by students of Grenoble INP — UGA and member of Pepit Ozer, the UGA startup incubator.
Deploy personalized deep learning models tailored to your asset universe. Our builder handles architecture optimization, so you can focus on the signal.
Transform complex logic into automated execution. Our event-driven directed graphs allow visual strategy construction with high-precision risk controls.
Bloomberg and LSEG give institutional teams access to data. QuantConnect and Axyon give them signals. None gives them a complete system that reasons across both structured and unstructured financial inputs, designs strategies automatically, and connects to execution.
The new wave of AI trading startups narrows individual gaps but deepens fragmentation. Composer handles strategy design. Auquan handles research. Vertus trades autonomously. No single platform covers the full stack without compromising on transparency, institutional access controls, or explainability.
Full competitive analysis arrow_forwardThe Kinetic LMM handles the complexity of financial data across ten specialized processing verticals — all in one unified model.
Categorize market regimes, sentiment polarity, and asset behavior with precision.
Predict future price action and volatility clusters across multi-scale time horizons.
Synthesize market scenarios and stress-test data for robust strategy validation.
Explainable AI providing the 'why' behind every signal and execution decision.
Identify systemic risks and hidden dependencies within the global financial graph.
Real-time exposure monitoring and tail-risk prediction for capital preservation.
Extract companies, assets, and market-moving events from unstructured text at scale.
Compress earnings calls, filings, and news into structured, actionable intelligence.
Query the model on any instrument, strategy logic, or macro condition in natural language.
Every component of Stratify is purpose-built to work as a unified system, from data ingestion to live execution.
PyTorch deep learning models, MLflow experiment tracking, configurable architecture builder, and hyperparameter optimization for financial time-series.
Event-driven directed graph execution, rule evaluation with state management, walk-forward backtesting with realistic fills, slippage, and commissions.
Real-time WebSocket + REST data connectors, paper trading simulation, broker integration (MetaTrader, IB), and latency-optimized execution under 100ms.