ForesightAI is a no-code quantitative research platform that validates your trading strategies the way institutions do — Walk Forward Analysis, Purged Cross-Validation, Monte Carlo simulation, and point-in-time data. Not just whether it was profitable. Whether it's deployable.
Standard retail tools answer one question: "Was this profitable historically?" That question is not the one you need answered before risking capital.
Testing on today's NIFTY50 ignores every stock that was delisted, merged, or dropped. Your backtest has no memory of those losses.
❌ INVALID UNIVERSEYour strategy "knew" about splits, bonuses, and index rebalances before they happened. That knowledge doesn't exist on the day you trade.
❌ FUTURE DATA LEAKOptimizing parameters on the full dataset produces a strategy that was tailored to noise. It has never been tested on data it hasn't seen.
❌ OVERFITTEDThree stages, each enforcing institutional-grade rules that prevent the common failure modes.
Compose entry/exit logic from 20+ indicators using a no-code drag-and-drop builder. Define position sizing, stop-loss rules, and declare which parameters can be optimized.
Walk Forward Analysis across rolling windows. Purged Cross-Validation with embargo gaps. Monte Carlo with 1000+ simulations. Stress-testing against 2008, COVID-19, and synthetic shocks.
Strategies that clear all validation gates move to paper trading against live data. One click to promote to live execution. The same logic runs in every environment — no drift, no surprises.
Most platforms end at metrics. ForesightAI forces your strategy to prove itself on data it has never seen, in market conditions it was never optimized for.
All features available in a single platform. No spreadsheets, no Python, no duct tape.
Compose multi-condition entry and exit logic using EMA, RSI, MACD, ATR, Bollinger Bands, VWAP, and more. No code required. Export as a compiled Strategy Artifact deployable across all environments.
PHASE 1Rolling train/validate windows across your full history. The optimizer only ever sees the training partition. OOS data is structurally inaccessible during parameter search — enforced at the engine level.
PHASE 11000+ trade sequence resamples to model the distribution of possible outcomes. Know your 5th-percentile drawdown, not just your average return. Make position sizing decisions based on realistic risk.
PHASE 1Run your strategy across all NIFTY50/100/500 constituents simultaneously. A strategy that only works on 3 of 50 stocks is not deployable. Median Sharpe, pass rate, and robustness score across the full universe.
PHASE 1Trade simulation runs in Rust — deterministic, fast, and memory-safe. The same engine that runs backtests runs paper and live trading. One codebase, zero behavioral drift between environments.
PHASE 1Promote validated strategies to forward testing on live NSE data. When paper results confirm live readiness, one-click deployment to real orders via Angel One and Zerodha. Full risk controls enforced before every order.
PHASE 2| Capability | Zerodha Streak | TradingView | Amibroker | ForesightAI |
|---|---|---|---|---|
| Walk Forward Analysis | ✕ | ✕ | △ Manual | ✓ |
| Purged Cross-Validation | ✕ | ✕ | ✕ | ✓ |
| Monte Carlo Simulation | ✕ | ✕ | △ Basic | ✓ 1000+ paths |
| Survivorship-bias-free universe | ✕ | ✕ | △ Manual | ✓ |
| Point-in-time corporate actions | △ Partial | △ Partial | △ Manual | ✓ Full chain |
| Reproducible results | ✕ | ✕ | △ | ✓ Versioned |
| No-code builder | ✓ | ✓ Pine | ✕ AFL | ✓ |
| Live execution (NSE) | ✓ Zerodha | ✕ | △ Broker API | ✓ Phase 2 |
We're onboarding a small group of traders and quants to shape the product before public launch. No commitment — just tell us whether you'd use this.
No spam. No marketing emails. One message when we're ready for you.