Quench provides an AI platform that ingests unstructured medical records and automatically creates structured, chronological timelines of clinical events. Its AskQuench natural‑language interface returns source‑cited answers to legal queries, allowing law firms and insurers to quickly extract diagnoses, procedures, and treatment gaps without manual document review.
Funding
Funding not disclosed
Founders
Product
Problem
Law firms and insurance companies must manually review extensive, unstructured medical records to extract relevant events, diagnoses, and treatment gaps for legal cases, a process that is time‑consuming, error‑prone, and difficult to scale.
Solution
Quench offers an AI‑driven platform that ingests medical documentation and automatically generates structured timelines of key clinical events. Its generative AI engine extracts diagnoses, procedures, and treatment gaps, then provides source‑verified answers to case‑specific questions through a natural‑language interface called AskQuench. The resulting chronologies and answers are delivered with linked source citations, enabling legal teams to quickly understand complex medical histories, build stronger arguments, and accelerate case review without manual document hunting.
Target Audience
Primary customers are law firms and insurance companies that handle medical‑legal cases requiring detailed analysis of patient records.
Features
- Physician‑engineered generative AI that parses unstructured medical records into chronological event timelines
- Natural‑language query tool (AskQuench) that returns instant, source‑linked answers to specific legal questions
- Automated extraction of diagnoses, procedures, test results, and treatment gaps with citation to original documents
- Secure, cloud‑based platform that supports bulk uploads and enterprise‑level access controls
- Exportable timeline summaries and reports that can be integrated into existing legal workflows