Inspiration

As a true crime enthusiast who watches movies like Zodiac and shows like Mindhunter, I always wondered about going through old cold cases and doing something about them. But mostly, all you can do is consume the content passively, not work actively like a detective. That's why I built IAM Detective.

What It Does

IAM Detective is a gamified web app that gives you the feel of a real detective investigating a real case. You go through an evidence pinboard, unlock clues, and test your theories. The AI helps you interrogate suspects and witnesses, while an AI co-detective guides you throughout the case like a partner.

How We Built It

Built using Next.js on the frontend and FastAPI on the backend. For the AI features, I used DigitalOcean's AI stack - storing all the case files, police reports, evidence reports, Wikipedia articles, and books into a Knowledge Base, then connecting an AI Agent to it. The agent is prompted to behave differently depending on the API call context: as a suspect, co-detective, or witness. It's also called to generate the evidence board automatically.

Challenges We Ran Into

  • Getting the AI Agent to function correctly across different personas
  • Long load times for case files
  • The evidence board not generating nodes properly

Accomplishments We're Proud Of

  • The full case is solvable end-to-end
  • User investigation progress is persisted across sessions

What We Learned

  • How to leverage AI Agents for multi-purpose, context-aware interactions
  • Connecting FastAPI with DigitalOcean's AI features
  • Deploying on DigitalOcean App Platform

What's Next for IAM Detective

Scaling it to support any publicly available real-life cases.

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