Muhammad Zeeshan Ahmed@zeesh

SpeciLoop is a synthetic-only, voice-assisted specimen handoff prototype designed to make every handoff explicit, verifiable, and reviewable. A surgeon states the complete specimen details, and AssemblyAI live transcription captures the spoken callout. A circulating nurse then performs an independent read-back and confirms the synthetic label code using manual entry or an optional camera scan. SpeciLoop’s deterministic verifier compares the laterality, anatomy, disposition, container count, read-back, and label code. If any required detail disagrees, the workflow is blocked and the discrepancy is clearly explained. When every field matches, the user reviews the combined evidence and submits a final confirmation. The server replays the submitted events and creates a stored evidence receipt containing a timestamp, receipt identifier, integrity hash, and technical limitations. The application is built with JavaScript and Node.js, stores receipts in Firestore, and is deployed on Google Cloud Run. SpeciLoop uses synthetic data only, is not intended for clinical use, and does not persist raw audio.

🌎 Online Hackathon | 💻 Month-long challenge | Dates: Sep 1–30, 2026 | 🏆 $10,000 Prize Pool ($5k cash + $5k in AAI credits) A month-long online challenge run by lablab.ai together with AssemblyAI, the Voice AI infrastructure company for builders. Every participant builds on AssemblyAI. You can join at any point — registration stays open for the whole build window, so you can start on day one or pick the project up halfway through and still submit. 🌍 Fully online hackathon. Join and build from anywhere in the world.