Real-Time AI Sports Analytics Platform Shipped in 3 Weeks — From Zero to 12,000 Active Users
SpeedMVPs built a Next.js web platform backed by a FastAPI ingestion service that consumed live SportRadar feeds via WebSocket, normalised raw event streams into a PostgreSQL + TimescaleDB schema, and served sub-200ms queries to the frontend. A fine-tuned GPT-4o layer generated plain-English tactical summaries and halftime predictions, with pgvector enabling semantic search across 3 seasons of historical match data. The entire stack was deployed on Vercel (frontend) and Railway (API + DB) with a configurable white-label embed for broadcast partners.
Sports / Media
Industry
3 Weeks
Timeline
Project Overview
1
What We Built
- SpeedMVPs built a Next.js web platform backed by a FastAPI ingestion service that consumed live SportRadar feeds via WebSocket, normalised raw event streams into a PostgreSQL + TimescaleDB schema, and served sub-200ms queries to the frontend. A fine-tuned GPT-4o layer generated plain-English tactical summaries and halftime predictions, with pgvector enabling semantic search across 3 seasons of historical match data. The entire stack was deployed on Vercel (frontend) and Railway (API + DB) with a configurable white-label embed for broadcast partners.
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