AI-Driven Trading Platform with Signal Intelligence
A production algorithmic trading platform combining quantitative signals, real-time news and sentiment analysis via LLMs, and execution management with built-in risk controls.
What Confidential fintech client was up against
The client wanted to augment discretionary trading desks with AI-driven signals that could combine structured market data, unstructured news, social chatter, and filings into a single actionable stream — without the hallucinations and blind spots that make most LLM-based trading systems unsafe in production. They also needed a clean separation between research (backtesting, model iteration) and live execution, with hard risk-management guardrails.
What we built
We built a two-layer system: a research layer (Jupyter-first, versioned datasets, backtesting engine, walk-forward validation) and a production layer (streaming market data ingest, LLM-powered news and sentiment pipeline, signal aggregator, risk module, broker execution adapter). LLM outputs are always grounded in retrieved source documents, with confidence scores gating whether a signal reaches execution. Circuit breakers, position limits, and daily loss caps are enforced at the execution layer regardless of signal recommendation.
What shipped
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