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DARKHORSE AI
Predictive intelligence that turns raw market signals into actionable edges.
Built front-end to backend to ML pipeline. Architect and Senior Engineer. Custom predictive model, real-time data ingestion, hypermetrics calculator, and a React UI that translates complex market signals into actionable intelligence. Live and operating.
- Client
- DarkHorse
- Role
- Architect & Senior Engineer
FEATURED
- E2E
- Front-end to ML pipeline
- Real-time
- Data ingestion
- Live
- In production
The Challenge
The data existed — endless streams of raw market signals — but no tooling turned it into decisions. Off-the-shelf analytics dashboards could chart the past; the client needed a system that could weigh the future, and needed it built end to end by one accountable engineer.
The Solution
As architect and senior engineer I built the full stack: a Python/TensorFlow predictive model, a FastAPI backend with real-time data ingestion, a custom hypermetrics calculator, and a React front end that renders model output as clear, actionable intelligence rather than raw probabilities.
The Outcome
DarkHorse AI is live and operating at darkhorsewin.com. The pipeline ingests continuously, the model scores in real time, and users act on its intelligence daily — a production ML system, not a notebook demo.
Highlights
- Custom predictive model designed, trained, and deployed for the platform's domain
- Real-time ingestion pipeline keeps predictions current as new data lands
- Hypermetrics calculator distills dozens of raw signals into a handful of decision-grade numbers
- React UI translates model output into intelligence a non-data-scientist can act on
Technology
PythonTensorFlowReactFastAPI
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