TradingView is for charts. This is for edge.
A Python-native quant platform with custom ML models, RAG over live market data, quantum portfolio optimization, and direct broker execution — all on one stack.
Pine Script can't run a transformer.
Every serious quant hits the same wall: charting platforms are great for pretty candles, but you can't deploy PyTorch, you can't query live filings, and you can't optimize a 500-asset portfolio on a GPU. We built the platform for the quants who outgrew the UI.
The Quant Stack
Six modules that together replace your notebook, your feed, your optimizer, and your broker API — with something actually production-grade.
Model Runtime
Deploy any PyTorch, TensorFlow, XGBoost, or scikit-learn model with zero glue code. Hot-swap versions, A/B test strategies, rollback in one click.
Live RAG Pipeline
Retrieval over live L1/L2 quotes, SEC filings, earnings transcripts, central-bank minutes, and news wires — vector-indexed and queryable in millis.
Quantum Optimizer
Hybrid quantum-classical solver for portfolio construction — handles 500+ assets, long/short constraints, and factor neutrality in under a second.
Tick Backtester
Tick-level replay with realistic slippage, queue-position modeling, and Monte Carlo stress tests across 20 years of historical regimes.
Execution Router
One API, every broker — Interactive Brokers, Alpaca, Zerodha, Kotak Neo, Binance. Smart routing, TWAP/VWAP, sub-10ms fill confirmation.
Risk Sentry
Real-time VaR, factor exposure, and drawdown alerts. Hard circuit breakers that kill strategies on regime shifts — before your P&L does.
From Signal to Fill
Six real-time stages the platform runs on every tick.
Ingest
Live feeds + alt-data.
Retrieve
RAG context per asset.
Predict
ML model inference.
Optimize
Quantum portfolio solve.
Execute
Smart broker routing.
Monitor
Risk & P&L live.
From Any Source, to Any Broker
Plug into the data and execution venues you already use — we handle the plumbing.
Built for Serious Capital
Four guarantees that separate a hobbyist toolkit from a production trading platform.
Sub-10ms Tick-to-Order
From feed arrival to order-out in under 10ms on colocated hardware. Latency budgets are measured, published, and SLA'd.
Deterministic Backtests
Same code, same data, same result — every time. No look-ahead bias, no survivorship, no surprises in production.
Quantum-Ready
Runs classical today. Offloads optimization to IBM Quantum, IonQ, or D-Wave when the problem fits — same API, no rewrite.
Institutional Controls
SOC 2, pre-trade risk, kill switches, audit logs, and segregated strategy sandboxes. Built for teams that answer to a CCO.
Strategies Running Today
A sample of what quants are shipping on the platform — names redacted for obvious reasons.
Cross-Asset Momentum with News RAG
A multi-strategy fund runs a transformer-based momentum model with live news-grounded regime detection across 200 futures and 500 US equities — re-optimized every 15 minutes via the quantum solver.
India Equities — Earnings Drift
A Mumbai family office ingests BSE/NSE filings the moment they hit the wire, runs an LLM-grounded sentiment model, and routes orders through Zerodha — fully automated, compliance-reviewed.
Crypto Stat-Arb on Perps
A prop shop runs a 40-leg statistical arbitrage across Binance and Bybit perpetuals — with the quantum optimizer rebalancing hedges every 30 seconds to stay delta-neutral.
Bring your notebook. We'll put it on live data.
Send us a Jupyter notebook with your signal. We'll deploy it to our paper-trading cluster with live L1 feeds and hand you a dashboard in 72 hours.
Stop renting charts. Start running strategies.
Python-native, quantum-ready, broker-integrated — the only platform that takes you from idea to live fills without a glue-code rewrite.