About StreamOracle

Transparent, multi-platform viewership analysis.

Mission

StreamOracle exists to bring transparency to live streaming viewership data. By collecting and analyzing viewer metrics across multiple platforms, we aim to provide the community with objective, data-driven insights into viewership patterns. Our goal is not to accuse anyone of wrongdoing, but to provide tools for informed analysis.

Open Source

StreamOracle is fully open source. Every algorithm, every weight, every threshold is visible in the codebase. We believe that transparency in our methods is essential for trust. Anyone can audit the code, propose improvements, or run their own instance.

View on GitHub

Disclaimer

Disclaimer

Suspicion scores generated by StreamOracle are statistical indicators based on data patterns. They are not accusations of viewership manipulation. Many legitimate factors can produce elevated scores, including but not limited to: raids, embeds, platform promotions, viral moments, and special events. Users should always consider broader context when interpreting results.

Tech Stack

Frontend

  • Next.js 14 (React)
  • TypeScript
  • Tailwind CSS
  • Recharts

Backend

  • FastAPI (Python)
  • SQLite + aiosqlite
  • APScheduler
  • httpx

Infrastructure

  • Docker & Docker Compose
  • Standalone deployment

Analysis

  • 7 independent detection signals
  • Weighted confidence scoring
  • Multi-platform support

Contributing

Contributions are welcome. Whether it's improving detection algorithms, adding platform support, fixing bugs, or enhancing the UI, your help makes StreamOracle better for everyone.

Check the GitHub repository for open issues and contribution guidelines.