Stealth is developing AI‑first technology for the fintech sector, aiming to apply advanced machine learning to financial markets and investment workflows. The team combines deep expertise in AI, engineering, and finance, with leadership experience from Google and other leading tech firms, to build scalable, high‑impact solutions for financial institutions.
Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions face increasing data volume and market complexity, making real-time analysis, trade execution, and risk management labor-intensive and prone to latency errors. Traditional tools often require manual model tuning and cannot scale efficiently with evolving market conditions.
Solution
Stealth provides an AI‑first platform that embeds scalable machine‑learning models directly into trading and investment workflows. The system continuously ingests market data, applies predictive analytics, and generates actionable signals that can be automatically routed to execution engines. Built‑in risk analytics evaluate exposure in real time, allowing institutions to adjust positions proactively. The platform offers API and workflow integrations that let firms replace or augment existing tools without extensive re‑engineering, delivering faster decision cycles and more consistent risk oversight.
Target Audience
Stealth targets institutional investors, hedge funds, and proprietary trading desks that require advanced analytics and automated execution capabilities within their existing trading infrastructure.
Features
- Real‑time market data pipeline with low‑latency preprocessing for high‑frequency environments
- Pre‑trained and customizable predictive models for price movement, volatility, and liquidity forecasting
- Automated trade signal generation with rule‑based execution routing to broker APIs
- Continuous risk monitoring dashboards that compute VaR, stress tests, and exposure limits
- Seamless integration via REST and FIX APIs, supporting existing order management and portfolio systems
- Scalable cloud architecture that auto‑adjusts compute resources based on workload demand