ALLDOQ is a cloud-based medical evidence management platform serving the UK medico-legal sector. It is designed to replace the combination of email, shared drives, separate imaging viewers, and spreadsheet-based time logs used by expert witnesses and instructing law firms with a single, auditable case workspace.

Key features and functions include:

DoqBuilder — Report Drafting
A structured report-writing tool that allows expert witnesses to draft court-ready reports using their own templates, headings, and boilerplate sections. Reports are exported as consistently formatted PDFs, with records and case chronology accessible within the same window during drafting.

DoqViewer — Integrated Radiology Viewer
A browser-based DICOM viewer that supports CT, MRI, X-ray, and ultrasound studies without requiring a separate application or plug-in. Users can apply window and level adjustments, pan, zoom, measure, annotate regions of interest, compare studies side by side, and insert marked-up imaging frames directly into report drafts.

Secure Document Hub
A structured repository for case bundles, GP records, hospital records, and correspondence, with granular role-based permissions and a full activity audit trail covering every view, download, and amendment.

Case Chronology
A tool that constructs a date-ordered medical timeline from underlying case records, with citations back to source pages, intended to support opinion formation and report drafting.

Time Recording and Invoicing
Integrated time tracking that allows experts to record time against each case as they work, with itemised timesheets and fee notes delivered directly to the instructing firm.

Instruction and Messaging
A secure in-platform messaging system that allows lawyers and expert witnesses to communicate, share queries, and manage supplementary instructions within the case file rather than via email.

DOQSynth — AI-Assisted Record Review
A separately deployed AI module that ingests medical record bundles in PDF format and extracts structured clinical facts — including medications, diagnoses, lab results, procedures, allergies, and encounters — into typed database tables. A case chronology is generated from the extracted facts, and users can query the record in plain language with every answer returned alongside a source document and page citation. DOQSynth is designed for self-hosted, single-tenant deployment and uses a layered reading approach (native text layer, page image, and vision model fallback) with a verifier stage to filter negations and wrong-patient attributions before answers are returned.