AI-powered medical record review platform for insurance and legal professionals. Takes unstructured medical records and produces structured, searchable summaries using NLP. Founded in Israel, HQ New York. $27.3M revenue, 82 employees (GetLatka 2025). $20M Series A. Acquired by Datavant for $200M (September 2025). Primary market is insurance but serves PI law firms — processes medical records for causation, damages, and liability assessment with pain score integration. Partnerships with Ontellus (medical record retrieval) and Datatrack. Multiple 2025 AI Excellence Awards. Mentioned on r/legaltech alongside Tavrn and other medical summary tools. Pricing per case model.
Company Info
- HQ: New York, NY, USA
- Team size: 82 employees
- Revenue: $27.3M (GetLatka 2025)
- Funding: $20M Series A
- Sector: AI Medical Record Review (Insurance + Legal)
- Acquired by Datavant for $200M (September 2025)
What We Haven’t Verified
This page was assembled from publicly available information. Post-Datavant acquisition, product direction may shift toward insurance/healthcare. r/legaltech reports are “mixed.” We have not independently tested the platform.
Workflows
Based on practitioner evidence, DigitalOwl is used in these workflows:
What practitioners struggle with
Real frustrations from legal professionals — the problems DigitalOwl addresses (or should address). Sourced from practitioner reviews, Reddit threads, and case studies.
Demand letter drafting takes 3-6 hours per case because the attorney manually weaves medical records, liability facts, and damage calculations into a persuasive narrative — multiplied across 50+ active PI cases
PI intake calls come in at 50-200 per week but 60-80% aren't viable cases — the firm wastes hours screening callers before a single billable minute, and good leads go cold waiting for callback
Where it fits in your workflow
Community Data
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