Built for traders who think in systems
Use Saral AI to turn trading ideas into strategy logic, backtest on historical NSE/BSE data, and deploy with confidence.
Illustrative backtest
CAGR+18.7%
Sharpe1.42
Drawdown-12.3%
Trades248
Figures shown are illustrative of the results view, not a live strategy.
The case for building this
Indian retail has the largest underserved equity market in the world — and the data on what goes wrong is public. Here is the evidence, and what we do about it.
Nine in ten lose. Now SEBI is closing the casino.
SEBI data shows 93% of individual F&O traders lost money over FY22–FY24. In response, SEBI's November 2024 clampdown is actively pricing retail out of F&O. Systematic cash equities are no longer just a smarter choice; they are becoming the only accessible one.
SEBI, Sep 2024 · 93% 02You are trading against machines. Now you can build your own.
In FY24, 96% of proprietary-trader profits and 97% of foreign-investor profits came from algorithms — while only 13% of individual traders used them. Retail brings manual decisions to an automated fight.
SEBI, Sep 2024 · 96% 03SEBI opened retail algo trading in Feb 2025. Walk through the door correctly.
For 13 years, algorithmic access was effectively institutions-only. SEBI’s February 2025 framework is the first to give retail a sanctioned path — through broker APIs, with rule-disclosed "white-box" strategies favoured.
SEBI Circular · Feb 2025Platform Features
Core systems for building, validating, and operating algorithmic strategies.
Visual Strategy Builder
Drag-and-drop nodes to define your universe, reconstitution pipeline, entry/exit criteria, and portfolio construction rules. Express multi-factor and multi-rule strategies as a visual pipeline. No Python, no pseudocode.
Explore module 02Strategy Templates
Start with proven, pre-built strategy templates and customize them to your investment thesis. Learn from tested approaches and make them your own.
Explore module 03Backtesting on 15+ Years of NSE/BSE Data
Test your strategies against 15+ years of historical NSE and BSE data. Our backtesting engine handles splits, dividends, delistings, and survivorship bias correctly.
Explore moduleStrategy Templates
Start from systematic ideas that already have structure, rules, and context.
Blank Canvas
An empty starting point. No filters, no rules — just a default NSE universe with equal weighting and weekly rebalancing. Start here when you want full control.
Inspect strategyDefensive Low Volatility
Defensive strategy targeting stable, well-established companies. Requires a large market cap (proxy for lower volatility) and selects the bottom 20 by recent price range (high-low spread) — stocks with the smallest daily swings.
Inspect strategy52-Week High Breakout
Targets stocks trading near their all-time highs — a breakout momentum strategy. Filters for stocks where close is within 5% of their all-time high, then selects the top 20 by market cap.
Inspect strategyInsights & Guides
Practical notes on backtesting, risk, execution, and systematic trading habits.
Bulk Deals vs Block Deals vs Shareholding Patterns
A bulk deal, a block deal, and a shareholding pattern filing each show a different, incomplete slice of who owns a stock. How to read all three.
Read guideFrom a Plain-English Thesis to an Editable Strategy
saral.money's AI assistant turns a plain-language investment thesis into an editable, white-box strategy flow — the same rule nodes you can open and change. What it does, why it stays inspectable, and what it deliberately does not do.
Read guideThe Indian Algo-Tooling Gap: What Streak, Tradetron and AlgoTest Can't Do
India's no-code algo platforms are either single-stock signal generators or options backtesters. None offer no-code, multi-rule portfolio backtesting on 15+ years of data. A fair look at the gap — and where each incumbent genuinely wins.
Read guideBuild your first strategy
Backtest against 15+ years of NSE/BSE data and deploy with confidence.
Launch Strategy Console