Inspiration
Inspired by doing this analysis manually as a lab assistant at Purdue, we built BioAnalysis.AI to make the process faster, clearer, and less error-prone.
What it does
BioAnalysis.AI helps users choose a safe biology analysis workflow from a text prompt, then shows a clear recommendation, key reasons, and a review step before running anything.
How we built it
We built it as a desktop app with React, TypeScript, Rust, and a bounded AI planner connected to an OpenAI API key, plus validation rules so the AI can only choose supported workflows.
Challenges we ran into
One challenge was keeping AI answers useful but still controlled, and another was handling unsupported requests without confusing users.
Accomplishments that we're proud of
We are proud that we made a clean approval flow, strong guardrails, helpful unsupported guidance, and solid tests for supported and unsupported paths.
What we learned
We learned that good AI products need clear limits, clear explanations, and good validation, not just model output.
What's next for BioAnalysis.AI
Next for BioAnalysis.AI, we plan to add more supported pipeline types, improve prompt understanding, and keep expanding tests while staying safe and reliable.
Built With
- react
- rust
- tauri
- typescript
- vite
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