Algo trading software built to SEBI's 2026 rules
Mintants builds custom algorithmic trading and trade-automation software for brokers, prop desks, RAs, and fintech startups — strategy engines, backtesting, broker API integration, and risk controls, engineered for the algo framework that became mandatory in April 2026.
- Algo-ID tagging ready
- Broker API integration
- Exchange-empanelment aware
Trading infrastructure that survives real market conditions
Not a strategy tip service — the engineering underneath. We build the systems that execute, log, and control risk when real money is moving.
Strategy & execution engines
Deterministic engines that turn a defined strategy into orders, with position sizing, entry and exit logic, and predictable behaviour under partial fills and reconnects.
Backtesting & simulation
Historical backtests with realistic slippage, brokerage, and latency assumptions, plus paper-trading so a strategy proves itself before it ever touches live capital.
Broker API integration
Production integrations with Indian broker APIs — Kite Connect, DhanHQ, Upstox and others — covering order placement, modification, positions, and live market data over WebSocket.
Risk controls & kill switches
Order-rate limits, daily loss caps, max position and exposure checks, and an operator kill switch — the controls SEBI expects and that keep a bad deployment from becoming a bad day.
Algo-ID tagging & audit logs
Every automated order tagged with its algo identifier at the broker level, with immutable execution logs that reconstruct exactly what the system did and why.
Dashboards & monitoring
Live P&L, open positions, strategy health, and alerting, so operators see problems while they are still small rather than in the end-of-day reconciliation.
From strategy spec to monitored production
A path that treats live capital with the seriousness it deserves — nothing goes live until it has proven itself in simulation.
- 01
Specify
We turn your strategy and operating rules into an unambiguous written spec — instruments, signals, sizing, risk limits, and failure behaviour.
- 02
Backtest
The strategy runs against historical data with realistic costs and latency, so its edge is measured rather than assumed.
- 03
Build
We engineer the execution system, broker integration, risk controls, and monitoring as production software with tests, not as a fragile script.
- 04
Paper trade
The full system runs live-but-simulated against real market data, proving behaviour under genuine conditions before capital is at risk.
- 05
Go live & monitor
Controlled rollout with conservative limits, live dashboards, alerting, and a kill switch — then we scale exposure as it earns confidence.
Engineering discipline applied to money in motion
Compliance-aware by default
We build to the current SEBI algo framework — Algo-ID tagging, broker-routed execution, and mandated risk controls — rather than retrofitting it after a regulatory notice.
You own the IP
Your strategy logic and your codebase belong to you. No lock-in to a black box you cannot inspect, audit, or take elsewhere.
Built for failure, not just the happy path
Reconnects, partial fills, stale ticks, and broker downtime are designed for up front, because these are the moments that actually cost money.
Fintech engineers, not generalists
A team that already understands order lifecycles, market microstructure, and the Indian broking stack — so you are not funding their education.
Questions about algo trading software
Straight answers on cost, compliance, and what automation can and cannot do.
Is algo trading legal in India?
Yes. Algorithmic trading is legal and regulated in India. Since April 2026, SEBI's framework for retail algo trading requires that automated orders route through a registered broker's API, carry a unique Algo-ID assigned at the broker level, and operate with mandated risk controls. Algo providers must work with a registered broker and cannot connect directly to the exchange.
What changed in SEBI's algo trading rules in 2026?
The framework brought retail algo trading formally into scope. Automated orders must be tagged with a unique algo identifier so the exchange can attribute them, algos offered to retail users need broker empanelment and exchange approval, and providers must implement order-rate limits and other risk controls. Security requirements such as static IP registration and two-factor authentication also apply to API-based automated access.
How much does custom algo trading software cost?
It depends on scope: a single-strategy execution system with one broker integration is a materially smaller build than a multi-strategy platform with backtesting, a user-facing dashboard, and several broker connections. We scope against your written strategy spec and give a fixed range before any build starts, rather than quoting a number that has to be revised later.
Which broker APIs do you integrate with?
We work with the major Indian broker APIs including Zerodha Kite Connect, DhanHQ, and Upstox, covering order placement and modification, positions and holdings, and live market data over WebSocket. If your broker exposes a documented API, we can integrate it.
Do you guarantee trading profits?
No, and you should be sceptical of anyone who does. We build and operate the software; market outcomes depend on your strategy and market conditions. What we are accountable for is that the system executes your logic correctly, respects its risk limits, and behaves predictably when things go wrong.
Can you automate an existing manual strategy?
Yes — that is a common starting point. We translate your discretionary rules into an explicit specification, surface the ambiguities that only appear once a machine has to follow them, backtest the result, and then build it. The specification step alone often clarifies the strategy.
Have a strategy that needs real infrastructure?
Tell us what you trade and how you want it automated. We'll tell you honestly what it takes to build, and what it will cost to run.