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This Is Deep Tech. And It’s Built Different
This Is Deep Tech. And It’s Built Different
We build explainable market signals by layering Attention mechanisms on top of traditional ML models, constrained by domain knowledge.
>What we are: A signal layer, not an execution or trading engine.
>Regulatory Compliant: Financial regulators in India and globally are pushing for explainable AI; unlike Blackbox systems, our systems offer better Explainability.
>Where we apply it first: Surveillance, anomaly detection, risk indicators, and directional calls.
>Data posture: built on high-fidelity feeds (NSE, Nasdaq, and select proprietary sources)
Not for Many. Just a Few.
We partner with a small number of institutions that can provide licensed data and require auditable, regulator-friendly signals.
We price our models based on the Level of Exclusivity the clients desire. A models signal may be shared with multiple Entities while some may be exclusive to just one Entity.
Roadmap $1M
Roadmap $1M
Duration: 15 to 18 months.
What We Will Achieve:
>Over the next 15–18 months we’ll develop 12–15 production-grade models using granular feeds from NSE (e.g., L2/L3 order books), Nasdaq (e.g., TotalView/ITCH), and proprietary providers under NDA. These will cover market surveillance, anomaly detection, risk forecasting, and directional signals.
>See every institutional move, identify iceberg orders, and anticipate market shifts.
>Demonstrate production-readiness (latency, robustness, explainability).
>License high-fidelity feeds solely for build/validation. For live use, institutions supply their licensed data and we deploy on our infrastructure passing only signals while withholding all model specs.
Objective: Validate causal + attention hybrid on multiple datasets; harden the pipeline (MLOps, latency, audit trails).
Deployment posture: PoC + pre-prod in our environment; live only with client-provided licensed data and infra.
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