TraderOps: The Trader's Operating System — Backtest, Paper & Live on One Engine
Built a multi-broker trading platform with paisa-exact backtest-to-live parity, a no-code strategy builder, and Telegram + MCP control across 6 brokers.
THWORKS built TraderOps, a full trading operating system that unifies strategy development, backtesting, and live execution on a single engine. Traders compose ORB, WAT, re-entry, and multi-leg option strategies without code, validate them on historical data with paisa-exact trigger alignment to live execution, then route orders across six brokers (Zerodha, AliceBlue, Tradejini, Zebu, Dhan, Delta). A hybrid stop-loss system combines broker-side orders with real-time monitoring, and the whole engine is controllable from Telegram and any MCP client — backed by kill switches, per-strategy capital limits, and daily position guards.
The Challenge
Retail and semi-professional options traders juggle a broker terminal for execution, a separate backtesting tool that never matches live fills, and manual spreadsheets for risk. Strategies that look profitable in a backtest fall apart live because the trigger math, slippage, and order-type behaviour differ. Managing stop-losses across multiple broker accounts by hand is error-prone, and there is no safe kill switch when a day goes wrong.
Disciplined, salaried traders want automation they can trust without writing code or babysitting a screen. The goal was one engine where a strategy is authored once and behaves identically in paper and live — so what you test is exactly what you trade — while remaining broker-agnostic and safe by construction.
Our Solution
TraderOps is a Python/FastAPI engine over PostgreSQL with a broker-abstraction layer that normalises order placement, modification, and reconciliation across every supported broker. SL/target/trailing trigger prices are anchored to the strategy's intent so the trigger ladder is bit-exact across live, paper, and backtest by construction — slippage moves the fill, never the trigger.
A single-orderbook reconcile loop is the only path that updates trade state from the broker, eliminating race conditions between per-order polling and event handling. Market data flows from one shared platform feed rather than per-user tickers, and execution is decoupled from the data source so any broker can execute against a common feed. Every action — Telegram command, MCP call, webhook, or scheduler — lands in the same audited trade pipeline.
Key Technical Decisions
Paisa-exact parity: trigger prices are anchored to expected entry so backtest, paper, and live produce an identical trigger ladder — the core trust guarantee of the platform.
Broker-agnostic layer: a frozen capabilities model per broker (tag format, product/exchange maps, order semantics) means engine code never branches on broker name, so adding a broker is additive and safe.
Control anywhere: a read/write MCP server and a Telegram bot let traders monitor and execute strategies conversationally, with a two-step confirm gate on every order-placing action.
Safe by construction: mode-scoped kill switches, per-strategy capital limits, and a scheduled MIS auto-square-off protect capital without manual intervention.
Results
Before
A broker terminal for orders, a mismatched backtester for research, and spreadsheets for risk — with backtest results that never held up live and stop-losses managed by hand across accounts.
After
One engine where a no-code strategy is authored once, validated with paisa-exact parity, and executed live across six brokers — controlled from Telegram or an AI client, with automated stop-losses and kill-switch safety.
Technology Stack
"TraderOps finally closed the gap between my backtest and my live trades. What I test is exactly what fires — down to the paisa — and I can manage everything from Telegram without staring at a screen all day."
Frequently Asked Questions
Common questions about this project and our approach.
SL, target, and trailing trigger prices are anchored to the strategy's intended entry rather than the actual fill, so the trigger ladder is computed identically in backtest, paper, and live. Slippage moves only the fill price — never the trigger — which keeps results paisa-exact across modes.
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