AI Medical Record Reviews for Insurance & Legal • InQuery

What

InQuery is an AI-enabled medical record review product focused on legal, insurance, and clinical casework. It is designed to turn large volumes of medical records into structured, decision-ready outputs so teams can identify material facts without manually combing through every page.

Based on the page content, the core workflow is: submit records (PDF upload or secure transfer), process and quality-check them, then review/search/export deliverables such as summaries, chronologies, and key facts. The positioning appears to be a high-stakes review platform for teams that need defensible case decisions, risk visibility, and faster record analysis.

Features

• Medical record structuring at scale: Converts large record sets into organized insights, helping teams review complex files more efficiently.
• Contradiction and risk surfacing: Highlights issues like prior injuries, conflicting details, and missing records to reduce downstream case surprises.
• Decision-ready outputs: Provides artifacts such as summary, chronology, and key facts to support legal and claims strategy work.
• Workflow from intake to export: Supports PDF upload/secure transfer, processing with QA, and export aligned to downstream review/reporting needs.
• Role-specific use across case functions: Presented for claims teams, IME/medical review, attorneys, retrieval/review operations, and cost containment groups.
• Security-oriented controls: States encryption, access controls, audit logs, and configurable retention for sensitive record handling.

Helpful Tips

• Validate output quality on representative files: Use a sample set with known contradictions and missing-document scenarios to measure practical review value before broad rollout.
• Define “decision-ready” standards internally: Align legal, clinical, and claims stakeholders on what must appear in summaries and chronologies for consistent case handling.
• Integrate QA checkpoints into existing SOPs: Since the platform includes automated processing plus human checks, map responsibilities clearly to avoid duplicate review effort.
• Prioritize highest-risk case types first: Start with matters where missed facts most directly affect exposure, causation arguments, or treatment-related cost decisions.
• Confirm security and retention fit: The page lists core controls, but teams should still verify policy-level and contractual requirements against their own governance standards.