Inspiration
League of Legends players live stories — triumphs, rivalries, and evolution across seasons — but their data rarely feels alive. RiftScribe was born to transform raw match stats into cinematic sagas using generative AI. The idea: What if every player had their legend narrated like a hero from Runeterra itself?
What It Does
RiftScribe connects to League of Legends match data, processes insights, and turns them into an AI-authored saga — complete with artwork and storytelling tone inspired by the player’s gameplay persona. Each saga features:
AI narrative chapters crafted from real stats
Dynamic fantasy art generated for each scene
Persona-driven storytelling (player chooses their archetype: strategist, duelist, mage, etc.)
API endpoint for developers to integrate storytelling into esports dashboards or fan pages
How We Built It
Frontend: Vite + React (for instant client rendering and story visualization)
Backend: AWS Lambda + API Gateway + Bedrock (for generative text and image AI)
Data Processing: Amplify + Node.js functions to fetch, clean, and summarize player data
AI Models: Claude for narrative logic, Titan Image/Stable Diffusion for fantasy illustrations
Hosting: AWS Amplify
Storage: S3 for saga and image persistence
Challenges We Faced
Debugging AWS Lambda’s missing credential chain and build artifact mismatch
JSON parsing of AI responses with variable structure
Maintaining CORS compliance across Bedrock endpoints
Balancing narrative creativity with gameplay accuracy
What We Learned
Serverless AI storytelling is viable at scale
Bedrock’s multimodal power simplifies orchestration across text + image models
UX needs “emotional hooks” — not just analytics — for player engagement
What’s Next
Personalized player dashboards with seasonal sagas
Integration with esports highlight reels (AI narrator mode)
NFT export of sagas as digital collectible scrolls
RiftScribe SDK for fan developers
Built With
- aws-amplify
- aws-bedrock
- aws-lambda
- claude-ai
- node.js
- reat+vite
- s3
- stable-diffusion
- titan-image-gen
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