Fragmented data
Prices, fundamentals, alternative data and research notes live in different systems, formats and frequencies. Cleaning and aligning them eats most of a researcher's week.
Now in early access
AI-powered analytics & decision support for quantitative finance
TradeGenAI unifies market data, quantitative research and risk analytics in one platform — with a language-model reasoning layer that explains every signal, so your team can move from data to a defensible decision faster.
signal-review / momentum_xs
AI analyst
Most of the out-performance comes from the last two regimes. Before sizing up, test sensitivity to transaction costs and check whether the factor exposure overlaps with your existing book.
The problem
Quant research is slowed down by everything around the model
Slow iteration
Every new idea means custom scripts, ad-hoc backtests and manual sanity checks — so promising hypotheses wait in a queue instead of being tested.
Hard-to-explain decisions
Signals and portfolio changes are difficult to justify to PMs, risk and investors when the reasoning is buried in notebooks and spreadsheets.
The platform
One workspace from raw data to decision
Data ingestion & normalization
Connect market, fundamental and alternative data sources into a single point-in-time store with consistent identifiers, calendars and corporate-action handling.
Signal research & backtesting
Define factors and strategies, run walk-forward backtests with realistic costs, and compare variants side by side with reproducible configurations.
Risk & portfolio analytics
Track exposures, drawdowns, correlations and scenario stress tests across strategies, so risk is part of the research loop instead of an afterthought.
AI decision copilot
A large-language-model reasoning layer, built on Anthropic's Claude, that explains signals in plain language, summarizes filings and research, proposes testable hypotheses and drafts decision memos — always grounded in your data and reviewed by a human.
How it works
Quant rigor first, AI reasoning on top
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01
Data
Ingest and clean multi-source data into a point-in-time research store.
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02
Analytics engine
Compute factors, backtests and risk metrics with deterministic, auditable code.
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03
AI reasoning layer
The language model interprets results, flags caveats and connects them to news and research.
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04
Human decision
Your team reviews a clear, evidence-backed memo and makes the final call.
Who it's for
Built for small teams doing serious quantitative work
Quant research teams
Shorten the loop from idea to validated backtest and spend time on research, not plumbing.
Emerging funds & prop desks
Institutional-grade analytics and risk tooling without building an in-house platform team.
Advanced individual investors
Systematic, data-driven tools and transparent explanations instead of black-box tips.
Team
Founder-led and building in the open
TradeGenAI is an early-stage startup. We are working closely with a small group of design partners to shape the platform around real research workflows.
Interested in early access or a design partnership?
Tell us about your data, your strategies and where your research process slows down.
founder@tradegenai.com