Institutional trading infrastructure.
Built for individual operators.
Precog closes the gap between quantitative desks and retail platforms. Design, deploy, and manage custom algorithmic portfolios — from a single strategy to coordinated swarms that trade together, balance risk together, and adapt with their own performance.
The tools that actually work are locked behind terminals and dev teams.
- Bloomberg-grade data: $24,000/year and a finance job
- Real algo infrastructure: a Python dev and six months
- No-code platforms: shallow, single-asset, template bots
- Retail platforms: charts and alerts, not intelligence
- Managed services: you lose control of your own money
- Institutional data and intelligence — no FactSet bill
- Real algo deployment — no Python, no scripting
- Multi-asset: futures, crypto, forex, Polymarket
- Trading terminal with AI-assisted execution
- You keep your account. You keep control.
Five context surfaces that institutional desks run on. Every one of them is wired into Precog.
Real-time forced-exit flow across every major perp venue.
Regime state detection — trending, ranging, volatility-expanding — per symbol and timeframe.
Positioning shifts, funding-rate divergence, and OI-driven flow reads.
Cross-venue sentiment aggregation, news and social signal integration.
Gamma exposure, dealer positioning, and flow-derived levels.
The edge isn't a new indicator. It's the context around price — who's getting liquidated, where positioning is stretched, what the options market is forcing. Precog treats that context as a first-class input, not a side panel.
Precog isn't one product. It's a platform with tracks.
Everything you need, integrated.
Run one algo or deploy a coordinated swarm. Precog treats strategies as a portfolio — balancing risk across positions, timing entries in context, and adapting allocations as each algo performs.
Every signal is generated against a live context layer — liquidations, regime state, open interest, sentiment, and option greeks. The same data a professional desk operates on, integrated into the strategy pipeline.
Three production-tested engines — Ultron, Clarity, FRIDAY — handle signal generation, research, and trade management. Use them as your full stack or plug them into your existing strategy.
Enter a trade. The algorithm manages it. Stop placement, scaling, exit timing — handled by the same intelligence running the automated strategies.
Futures, crypto, forex, Polymarket. Same interface, same controls, multi-account support for both personal and managed setups.
Trade on the platforms you already trust.
Precog connects to your broker via read-execute API. No fund transfers, no custody, no lockups. Your account. Your capital.
Run one algo. Or a swarm of them, coordinated.
Precog isn't built around a single strategy. It's built around algorithmic portfolios — custom baskets of strategies designed to trade together. Run one algo if that's what you want. Run a swarm of thirty if that's what the thesis needs.
Select from the active strategy library, bring your own, or mix both. Every portfolio is a custom configuration — asset mix, risk ceiling, correlation rules, capital allocation.
The platform manages the basket — balancing exposure, respecting account-level risk limits, and sequencing entries so strategies don’t step on each other.
Each strategy tracks its own performance. Allocations shift toward what’s working, away from what isn’t, inside the risk envelope you set. Portfolio-level circuit breakers enforce discipline.
If you want a single algorithm running in a single account, the platform handles that cleanly. If you want thirty algorithms coordinated across five accounts with per-strategy risk rules, the platform handles that too. The infrastructure is the same. The scale is your call.
The platform, running in production.
Bots running today. Trades closing today. Everything shown here reflects actual tracked performance — live or forward-tested, no curated marketing reels.
Live and forward-tested results shown. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for every investor.
Precog is built and operated by a working trader.
Precog exists because the gap between retail trading tools and institutional infrastructure is unreasonable. Retail platforms stop at charts and alerts. Code-first quant tools assume you have the engineering time to build. The systems that actually move markets sit behind seven-figure enterprise contracts and hiring desks that don't care about individuals.
The platform was designed from the seat of an active trader — with the data surfaces, risk controls, and execution quality that professional desks treat as standard. Nothing about the product is aspirational. Every feature is in the platform because a working trader needed it.
Access is deliberately controlled. Cohorts are small, reviewed individually, and scaled against the architecture's operational limits — not a revenue target.
One firm runs their entire client operation on Precog.
WSP Capital delivers automated futures trading to accredited clients. Twelve strategies. Two years live. Every trade executed through Precog's infrastructure.
“Precog is what the managed-trading stack should have looked like ten years ago. We built WSP on it because everything else required us to be a software company first.”— WSP Capital
We open the platform in cohorts. Here's why.
A trading platform isn't a consumer app. More users doesn't make it better — in fact, it makes onboarding shallower, support slower, and community quality worse. We'd rather have a smaller number of operators who get the platform's full attention.
Every applicant is reviewed personally. If you're a fit, we'll reach out when your cohort opens.