Deployed in the markets: $2.5m

AI
in the Markets.

Quantegies is an AI research lab deploying next-generation quantitative strategies into global markets. We bridge the gap between deep learning and alpha generation.

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Our Thesis

Markets are not random walks.
They are high-dimensional physics problems.

For decades, quantitative finance has been dominated by "Quant 1.0": linear regressions, statistical arbitrage, and mean reversion. These methods assume markets are stationary and noise is normally distributed. In a hyper-connected world, these assumptions are collapsing.

We believe we are entering the "AI Native" era of finance. Just as LLMs learned the underlying structure of language, our Foundation Models for Finance (FMFs) are learning the latent physics of price action.

By treating the entire market history not as a spreadsheet, but as a sequential language problem, we can identify non-linear causal chains that are invisible to traditional statistical methods.


Fundamental

Human intuition. High latency. Unscalable.

Statistical (Quant 1.0)

Linear models. Feature engineering. Crowded trades.

Generative (Quantegies)

End-to-end Deep Learning. Emergent strategies. Adaptive.

Beyond Statistical Arbitrage

We don't just fit curves. We build agents that understand market microstructure.

Temporal Transformers

Adapting the attention mechanism to financial time-series. Our architectures can attend to distant regimes to contextualize volatility and liquidity dynamics in real-time.

Counterfactual Simulation

We generate synthetic stress regimes to validate robustness, tail behavior, and failure modes before deploying capital.

Neural Execution

Execution policies optimize for fill quality and impact under microstructure constraints, learning when to provide or take liquidity.

Multi-Modal Ingestion

We combine market data with alternative signals when it improves predictive power and stability across regimes.

Self-Optimizing Infrastructure

Elastic compute that shifts capacity between training and inference based on volatility and market regimes.

Research Platform

BAQLABS is our realistic research stack.

A Institutional grade environment for validating strategies under market microstructure constraints that is built to reduce the gap between backtest and live deployment.

Queue-aware simulation Latency controls Order book analytics C++ / TypeScript
Baqlabs platform UI

Strategy Builder

www.baqlabs.com

MBO replay · Queue analytics · Latency Lab · Model Lab · Results

Join the Lab

We are a small team of researchers and engineers solving the hardest problems in finance. We are currently hiring for the following roles.

Don't fit these exact roles? Email us your CV anyway.