Algo Trading Platform
Automated strategies, your broker, your control
- Industry
- Fintech · Trading automation
- Status
- Live
- Our role
- Design, engineering and operations
- Services
- AI & Intelligent Automation, Web & Product Engineering, Software Engineering
Overview
A cloud algorithmic-trading platform: build strategies without code, backtest them, paper trade by default and go live through the trader's own broker, with AI research running alongside.
The problem
- Manual execution is slow and emotional; active traders cannot watch charts all day.
- Testing an idea usually means writing code, and going live too early is costly.
- Equity and crypto usually live in two separate worlds.
The approach
One Strategy Builder where traders compose rules from forms and settings, then backtest, paper trade and only then go live, with explicit consent. The engine runs on the server during market hours, so the trader's laptop does not have to.
System architecture
01
Strategy Builder
Point-and-click rules: indicators, opening range, risk settings
02
Backtester
Historical simulation on any stock, index or index basket
03
Execution engine
Fetches candles, evaluates signals, monitors stop-loss and targets every few seconds
04
Broker adapters
Angel One (Indian derivatives) and Delta Exchange (crypto, 24/7)
05
AI layer
Live Research on a 5-minute cycle and Swing Trade AI, with multi-provider LLM failover
06
Trust layer
Paper by default, recorded live consent, audit log, encrypted broker tokens
Technology
- React
- TypeScript
- Vite
- TanStack Query
- Node.js
- MongoDB
- AWS Amplify
- Groq · NVIDIA · OpenRouter LLMs
Key features
- No-code Strategy Builder with backtesting before any live order
- Paper trading by default; live trading only after recorded consent
- Trade guards, cooldowns and database-level duplicate-trade prevention
- AI Live Research cards with entry, stop-loss and targets, placeable in one click
- Swing Trade AI with a dedicated position monitor
- Telegram and WhatsApp alerts; audit log for logins, consent and mode changes
- Starter, Pro and Ultra Pro plans billed monthly, half-yearly or yearly
Challenges solved
Model layers that fail silently
A single LLM provider can go down or rate-limit without warning. The AI layer runs an environment-driven provider chain with per-attempt timeouts, an overall deadline, failure classification and per-provider cooldowns, so one outage degrades a feature instead of killing it.
Duplicate or runaway trades
Guards live in the database, not just in code: partial unique indexes make a second identical order impossible even under concurrent signals.