Evidence-linked medical record review. MedRecordXpert converts multi-thousand-page record packets into a structured longitudinal dataset and a clinician-oriented summary where every claim carries a page-level citation — making full review feasible in hours instead of weeks.
Complex patients and med-legal cases arrive as record packets thousands of pages deep — scanned, unordered, and mixed across providers and decades. A full read isn't feasible, so professionals skim. And the one abnormal result from 2019 stays buried on page 3,080.
Generic AI summarizers make the risk worse: a summary with no path back to the source page can't be trusted for care decisions or defended in a legal review. What's needed isn't a shorter version of the chart — it's a structured, cited view of all of it.
MedRecordXpert dramatically reduces time-to-context by converting the entire packet into structured, source-cited data — with uncertainty, contradictions, and gaps flagged instead of smoothed over.
The sequence below is the actual processing pipeline, run per patient in an isolated project.
Each patient gets an isolated project. Upload the packet — native or scanned PDFs, mixed sources — and the system splits and stages every page for processing.
High-throughput OCR converts printed pages to machine-readable text, with an optional handwriting pathway that can be enabled when the packet calls for it.
Labs, vitals, medications, diagnoses, and procedures are extracted into structured rows — each row stamped with the source document and page it came from.
AI row mapping organizes findings across time and providers. Internally inconsistent values are flagged as requiring reconciliation; absent results are listed as missing — never inferred.
Clinician-oriented summaries are generated by specialty, body system, and record type — and every claim in them carries its page-level citation back to the source.
A cited Word summary for review plus a longitudinal Excel dataset of every extracted value over time. Runs in batch, with checkpoint/resume for very large packets.
Every summarized finding links back to its source document, page, and extracted row — so a reviewer can move from any claim to the original record in seconds.
Extraction assigns every finding a row ID, and summarization is checked against that inventory — no extracted findings are dropped on the way into the report.
Internally inconsistent values are flagged as requiring reconciliation. Missing results get their own section. If a record is missing, the system can't invent it — it flags it.
Every extracted value lands in a dated, sourced dataset — so trends across years and providers are visible instead of scattered through the packet.
Parallel workers tuned to your workstation process thousands of pages in hours. Batch mode handles caseloads; checkpoint/resume protects long runs from interruption.
Built for the packets reviewers actually receive: scanned and native PDFs, mixed providers and formats, with an optional handwriting OCR pathway configurable when needed.
MedRecordXpert processes and stores records locally on your workstation — patient files are not uploaded to an XpertWorx cloud. AI analysis runs through your organization's own model-provider account, configured with a HIPAA Business Associate Agreement and zero-data-retention, with traffic encrypted in transit. You control storage, retention, and access on your own hardware, inside your own compliance program.
Intended use: MedRecordXpert is a documentation and decision-support tool for licensed clinicians and qualified professional reviewers. It does not provide autonomous diagnosis, its outputs may contain errors, and it is not a substitute for clinician review of the chart. Every report is designed to be verified — that's why the citations are there.
The failure mode of AI in medical review isn't slowness — it's confident fabrication. MedRecordXpert is engineered the opposite way: it surfaces uncertainty, contradictions, and missing documentation instead of papering over them.
Built on the record-processing engine proven across XpertWorx's claims platforms — and reviewed against the questions clinicians, compliance officers, and opposing counsel actually ask.
| Deployment | Local processing and storage on your Windows workstation — per-patient project isolation; PHI stays in your environment. |
|---|---|
| AI access | Runs through your organization's own model-provider account with a HIPAA BAA and zero-data-retention configuration; encrypted in transit. |
| Inputs | Scanned and native PDF record packets across providers and formats; printed-text OCR standard, optional handwriting OCR pathway. |
| Outputs | Clinician-oriented Word summaries by specialty and body system with page-level citations; longitudinal Excel dataset of extracted values. |
| Throughput | Approximately 4,000 pages in a few hours on a capable workstation; parallel workers configurable to your hardware; batch processing supported. |
| Reliability | Checkpoint/resume on long runs; row-ID coverage tracking from extraction through summarization. |
| Economics | Typical AI cost of $10–15 per report at current model pricing, visible per run. |
| Program status | Early access — onboarding clinical, med-legal, and claims-review partners now. |
* No extracted findings are dropped during summarization; coverage is tracked by row IDs from extraction through report generation.
Onboarding complex patients with decades of records from multiple health systems.
Independent medical examiners and expert reviewers who must account for the entire packet — and cite it.
VA and SSDI claim preparation on evidence-heavy files — a natural companion to VetXpert and SSDI Xpert.
Teams building an accurate longitudinal picture across fragmented provider records.
Join the early-access program or request a redacted sample report to see the citation workflow firsthand.