# Caliper

- **Event:** [Google I/O Hackathon](https://cerebralvalley.ai/e/google-io-hackathon)
- **When:** Sat, May 23 at 9:00 AM – 10:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Tobasum Mandal](https://cerebralvalley.ai/u/tobasum)
- **GitHub:** https://github.com/tobasummandal/caliper
- **Demo video:** https://youtu.be/373V-WSEU8U
- **Gallery:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery/87

Helios is a multi-agent system that catches silent bugs in scientific Python: the kind that don't crash but produce wrong-looking-right results (off-by-one errors in numerical integration, unit mismatches, broken boundary conditions, subtractive cancellation).
Built on Gemini 3.5 Flash, Helios deploys four specialized sub-agents in a long-horizon workflow with a researchers-in-the-loop flywheel:

- Auditor: combines static analysis (ast/libcst) with Gemini-driven semantic review to catch numerical instability, unit mismatches, and shape assumption errors
- Fixer: regenerates corrected code per accepted issue
- Verifier: synthesizes test inputs (random within type-inferred bounds, edge cases, large-N stress), runs original vs. fix in isolated sandboxes, and rejects fixes that don't pass, triggering regeneration
- Router: flags hot loops (Monte Carlo, FFTs, matmuls, nested numeric loops) for GPU or quantum dispatch with estimated speedup

Researcher review of accepted/rejected fixes feeds back into the system, creating a continuous improvement loop.
What's never been built before: other AI coding tools generate fixes; Helios is the first multi-agent system that verifies its own fixes against synthesized tests before showing them to you, and the first to combine correctness verification with hardware-aware routing in a single agent pipeline. The target users are scientists, not software engineers, the audience whose bugs end up in published research.

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