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Event extraction for Medical Researchers
Talc helps hospitals pull events and data out of messy EHRs.
Talc AI provides expert quality medical abstraction powered by large language models for medical researchers. The focus is on event extraction in medical research contexts.
The product leverages large language models to perform expert-quality medical abstraction, enabling event extraction tailored for medical researchers. It processes medical text to identify and extract relevant events and insights, delivering structured outputs that support research workflows.
Who it’s for: medical researchers, biotech/pharma research teams, academic researchers
Ex-Airbnb, Ex-FB SWE. At Facebook I worked on Election Integrity, using graph algorithms to detect coordinated activity, from foreign election interference to terrorist propaganda. At Airbnb I worked on moonshots that will (maybe) ship late 2023. When I'm not working you can catch me snowboarding or climbing!
Formerly doing privacy at FB and security at Microsoft. I was the tech lead for a 30 person engineering team at Facebook, and was involved in the privacy side of most major product launches over the last two years. I founded Talc to help people turn AI tech demos into production apps, along with my long time friend and climbing partner Matt.
Replay sessions, tweak inputs, and take the guesswork out of AI debugging.
Talc.ai launches an LLM debugger that lets users replay prior AI sessions, edit inputs and prompts, and run regression tests to understand and improve AI behavior. It targets developers debugging production LLM systems by removing manual copy-paste and enabling quick context-focused fixes.
From the original launch (Jul 2023) — may be outdated.
Formerly “Homey”
Medical language models to automate healthcare operations
AI Inference Platform for Drug Discovery
