Inspiration
We wanted to make sports data come alive — not just numbers, but stories. Inspired by highlight reels and post-game analysis, we aimed to create a system that uses AI to generate interactive “rewinds” and insights for players and matches.
What it does
Rift Rewind is an AI-powered sports analytics platform that transforms raw match data into interactive insights, visual summaries, and rewinds. It analyzes players, matches, and full seasons using generative AI, creating shareable and engaging performance overviews.
How we built it
We combined AWS Lambda with secure data handling, integrated GenAI models like Bedrock and Gemini for analysis, and built a dynamic sharing module with smart widgets for distributing insights. Data is processed into structured JSON files to enable fast rewind generation and yearly player summaries.
Challenges we ran into
Ensuring secure credential management, scaling AI analysis for large datasets, and optimizing Lambda performance were major challenges. Balancing analytical depth with real-time rendering also required careful system design.
Accomplishments that we're proud of
We achieved seamless AI-driven rewinds for matches and players, developed a robust sharing system, and improved user experience through clear, visual insights. The integration of multi-match analysis and timeline views was a key milestone.
What we learned
We learned how to leverage generative AI for data storytelling, optimize cloud-based workflows, and design AI insights that are both technically sound and visually engaging.
What's next for Rift Rewind
Next, we plan to expand multi-season analysis, integrate real-time match tracking, and enhance personalization — giving every fan and analyst the ability to explore, share, and relive game stories powered by AI.
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