How are documents stored and retained?

Documents are processed in memory and are not saved by the application, and the extracted data you review and export is what your own systems keep. Hosting, any external AI or OCR processors, logs and retention periods are agreed during implementation.

Where do extraction, summarisation and interpretation end?

Extraction pulls structured fields from the record, and summarisation consolidates them into one view for review. Each value links to its source for verification, and clinical interpretation and decisions stay with clinicians.

What is available today, and what is configured?

Available today: extraction from PDFs, scans, photos, Word and text files, source-linked review and a consolidated patient summary. Configured during implementation: hosting, export formats and connections to your clinical or claims systems. Not claimed: handwriting support and clinical recommendations.

How is patient data protected?

Documents are processed in memory and are not saved by the application. Access is role-based. Hosting, any external AI or OCR processing and logs are agreed during implementation, and deployments are configured for the data-protection law that applies to you, such as India's Digital Personal Data Protection Act.

Healthcare document intelligence · by aQb Solutions

Clinical Document Extraction AI with Source-Linked Review.

Clinical Document Extraction AI is medical document processing software that turns clinical documents into structured, source-linked data.

Video transcript

Around 80 percent of medical data stays unstructured, locked in PDFs, scans and clinical notes. Reading every document by hand is slow, and one missed detail can delay a decision. Medical Document Extraction by aQb Solutions turns clinical documents into structured, reviewable data for hospitals, health insurers and clinical research teams. Upload a PDF, scan, photo, Word or text file. It is read, classified and extracted automatically, with AI OCR for scans and photos. In review, the original sits beside the extracted fields, with a source link for every value. Browse diagnoses, medications and labs, with abnormal and critical values flagged, then confirm or correct each field against its source. Then combine documents into one patient summary, with active problems and medication reconciliation. Documents are processed in memory and never stored. Clinicians stay in control of every value. The document shown is a sample. Read faster. Trust every value. Decide with confidence.

Clinical Document Extraction AI by aQb Solutions (shown in the film as Medical Document Extraction) is medical document processing software that turns PDFs, scans and photos into structured data for hospitals, health insurers and clinical research teams, with a source link behind every value. Read faster and check every value: it first extracts structured clinical data (patient details, diagnoses, medications and labs) from PDFs, scans, photos and Word files, and links each value to its source for review. It then consolidates the reviewed data into one patient summary. Clinicians confirm or correct each value, and clinical interpretation stays with them.

It extracts and summarises. It does not diagnose, recommend treatment or replace clinical judgement.

Impact you can measure

Illustrative targets, not measured results. Actual results depend on document types and quality, and are measured in a pilot on your own documents.

30 min → 2 minTarget time to review one clinical document

70%+Target reduction in manual data entry per patient record

Hours → MinutesTarget time to consolidate a multi-document patient record

Days → Same dayTarget turnaround for a patient summary

Every fieldExtracted with a source link to check it against

1 viewEvery uploaded document in one patient record

What it does

AI clinical document extraction

Reads PDFs, scans, photos, Word and text files, using AI OCR for scans and photos, and identifies the patient, encounter and document type.

Structured clinical data

Segments each document into medical history, diagnoses, medications, allergies, procedures, investigations and lab results.

Medications, labs and critical findings

Captures medication, dose and frequency, and lab results with units and reference ranges, flagging abnormal and critical values.

Source-linked values

Each value links to its source text, shown side by side for checking. A link supports verification; it does not prove a value is correct.

Human review

Clinicians confirm or correct each field against its source, and clinical decisions stay with them.

Patient summary and medication reconciliation

One summary of active problems and medications across documents, with discrepancies flagged for a clinician. Follow-up plans come from the source documents.

Key Questions Answered

01 / 05

Can it process scanned and handwritten records?

It reads PDFs, Word and text files, and uses AI OCR for scans and photos. Handwritten records are not claimed as supported until they are tested on your documents.

How it works

01Upload Documents
02AI Document Processing
03Patient Identification
04Clinical Segmentation
05Data Extraction
06Critical Findings
07Consolidated Summary
08Human Review

Technology stack

OCR & Document Intelligence
NLP & Clinical Information Extraction
Python
FastAPI
React.js
Vue.js
Laravel
PostgreSQL
MySQL

Use cases

01Hospitals

One patient view from scattered records

Turn PDFs, scans and photos into a structured summary of diagnoses, medications and labs, with clinicians confirming each value against its source.

02Faster medical record assessment

02Health insurance

Faster medical record assessment

Extract diagnoses, treatments and investigations from submitted records, with a source link behind every value for the assessor to check.

03Consistent patient-level data

03Clinical research

Consistent patient-level data

Structure information from clinical documents into consistent datasets, built only from reviewed, source-linked values.

Want to see Clinical Document Extraction AI on your own clinical documents?