Bet.AI
Scan any bet slip. Get instant AI analysis.
◼ Walkthroughs
◼ Live demo
◼ Architecture
Expo SDK 52 frontend with a Firebase backend (Auth, Firestore, Storage, ~7K LOC of Cloud Functions). Six sports data providers feed parallel pipelines covering NBA, NCAA basketball, NFL, NCAA football, all major EU soccer leagues, MMA/UFC, and tennis Grand Slams. A custom CatBoost model deployed on Google Cloud Vertex AI computes 88 engineered features per prediction, hitting 70%+ accuracy on high-confidence interval player prop calls.
◼ Features
Bet slip scan
Image captured via camera or gallery, OCR'd by GPT-4 Vision, then parsed into typed bet slip data and rendered as a structured analysis.
Six-source data aggregation
Parallel pipelines pull from The Odds API, SportsGameOdds (with key rotation), API-Sports, StatPal, API-Tennis, and WeatherAPI per request.
Custom ML props model
CatBoost on Google Cloud Vertex AI. 88 engineered features per prediction from real-time player game logs. NBA and soccer props hit 70%+ accuracy on high-confidence interval calls.
Multi-sport coverage
NBA + NCAA basketball, NFL + NCAA football, all major EU soccer leagues, MMA/UFC, and tennis Grand Slams + main tournaments.
Match intelligence layer
Recent form, head-to-head, momentum, x-factors, and a written AI breakdown surfaced alongside odds and value ratings on every analysis.
Real-time orchestration
~7K LOC of Firebase Cloud Functions running parallel async calls per analysis. Firestore cache layer with TTL controls keeps response time low across six external APIs.