Workers' comp claims depend on an Independent Medical Examination (IME).
When someone gets injured at work, an independent physician reviews the entire case and writes a report on what happened, how severe it is, and what treatment makes sense. It carries real legal and financial weight, and it has to hold up if it's challenged in court.
Take the manual work out of the process without taking the physician out of a single decision.
A single case can involve dozens of PDFs spanning hundreds of pages of treatment history.
Conditions, medications, ICD-10 codes, dosage changes, test results, timelines - all buried across documents.
Every claim must trace back to source document, page, and passage. Physicians track this mentally or with sticky notes.
Most AI platforms cannot legally handle PHI. The shortcut tools are off the table from day one.
We find the software that already solves it, vet it against how you work, and get your team running on it. Live in days.
We connect the tools you already use so the manual steps disappear and data moves on its own.
We design and develop something custom from the ground up. Built for how your business runs, owned by you.
We tell you when holding is smarter. You leave with a clear reason and a date to revisit.
Before we recommend anything, we score the project on three things: how unique the work is, what a mistake costs, and how much of it runs on human judgment.
Case files upload straight to a HIPAA-compliant S3 bucket using temporary Cognito credentials. The server never touches the file bytes.
OCR and layout analysis, medical entity recognition with ICD-10 and RxNorm codes, semantic chunking, and 1024-dim embeddings, all indexed in PostgreSQL.
Hybrid search blends semantic and keyword matching, then passes the top results to Claude. Every answer comes back with inline citation chips.
A preliminary IME report builds automatically, mapped to standard template sections, with every fact cited to its source document, page, and exact location.
The physician reviews, edits, and moves the report through each stage. Every edit is logged with full version history.
Final reports export to PDF or Word with traceability footers built in. Download requires custody-transfer acceptance, the point where liability passes to the physician.
Physicians submit structured feedback on each case. Admins turn it into a Change Log tied to real software updates, closing the gap between "the AI got this wrong" and "here's what we fixed."
| Metric | Before IMEAI | With IMEAI |
|---|---|---|
| Fact extraction per case | 2 to 4 hours, manual | 5 to 10 minutes, automated |
| Preliminary report drafting | 3 to 5 hours from scratch | Minutes, AI-generated with citations |
| Citation verification | Mental tracking and sticky notes | Click to source in under 3 seconds |
| Medical coding | Manual lookup | Automated ICD-10 and RxNorm with confidence scores |
| HIPAA compliance | Multiple tools, varying compliance | Single BAA boundary, unified audit |
| Model flexibility | None | Swap models and prompts without code |
Every component had to clear the BAA boundary. HIPAA by architecture, not by policy.
Preserves page geometry and bounding boxes - the raw material for source citation highlighting. HIPAA-eligible under the AWS BAA.
Domain-specific medical entity extraction. Returns standardized ICD-10 and RxNorm codes with confidence scores. A general LLM would invent codes; this one returns the real ones.
Embeddings that never leave the BAA boundary. No external embedding API calls. Optimized for semantic search across heterogeneous medical documents.
Vector storage co-located with relational data. No separate vector database to secure and audit. Single HIPAA compliance surface.
HIPAA-eligible Claude inside the AWS BAA. Model-agnostic - Opus, Sonnet, and Haiku interchangeable based on case complexity.
Merges semantic and keyword search results without score normalization. Catches both conceptual matches and exact medication names.
| Network | All AI services accessed via VPC endpoints - no public internet traversal. |
| Storage | SSE-KMS encryption, versioning, Block Public Access, Object Lock on final reports. |
| Compute | ECS Fargate in private subnets, no SSH, no persistent storage. |
| Database | KMS encryption at rest, TLS in transit, pgaudit for query logging. |
| Application | Laravel encrypted casts for PHI columns, append-only audit_logs table. |
| Access | Cognito MFA, JWT with role claims, case-level isolation. |
Have a workflow with stakes this high?