Technology Powered by Advanced Neural Networks — How Quantum AI Works
The Quantum AI engine is a stack of transformer-based models trained on twelve years of NSE and BSE tick data alongside a curated set of international forex, index, and commodity feeds. Each model in the stack specializes in a regime — trending, mean-reverting, or volatility-driven — and a meta-controller routes capital to whichever sub-model has the highest current confidence score.
Market data ingestion runs continuously: order-book depth, trade prints, cross-asset correlations, and macro news vectors are fed into the inference layer with sub-millisecond latency. Inference does not block on the network round-trip to your account because the entire signal pipeline lives inside the platform.
Signal generation is decoupled from execution. A signal becomes an order only after it passes the risk gate, which checks against your configured drawdown limit, current exposure, and the live volatility regime. The gate rejects perfectly good signals if the moment is wrong — that selectivity is what holds drawdowns in single digits during turbulent weeks.
Execution lives behind a partner broker layer that abstracts venue, fees, and slippage. The platform does not custody your funds; it simply directs the broker layer with instrumented orders. Every trade is logged, attributed, and exposed to you through the reporting dashboard.
- › Sub-millisecond inference latency
- › Twelve years of NSE/BSE training data
- › Transformer architecture with regime-aware routing
- › Risk gate evaluates every signal before execution