Clinical documents turned into usable patient context.
Faurenis Document Intelligence helps dental teams read uploads, classify documents, extract relevant information, and surface what the chart may be missing.
Anything you upload, classified at intake
- Panoramic
panoramic-2026-09-13.pdf
- Blood test
cbc-blood-panel-2026-09-04.pdf
- Lab report
lab-hba1c-2026-08-21.pdf
- Periapical
periapical-#36-2026-07-12.pdf
- Intake
intake-marija-h-2026-05-02.pdf
- Referral
referral-dr-novak.pdf
- Rx
rx-amoxicillin-500.pdf
Extracted preview
panoramic-2026-09-13.pdf
Panoramic radiograph
- Patient ref
- PT-04219
- Date taken
- 2026-09-13
- Findings
- #36 carious · #46 monitoring
- Source page
- p.1 of 1 · retained
Radiographs, blood panels, lab reports, intake forms, referrals, prescriptions, consents — every upload classified, extracted, and routed to a clinician-reviewed queue with the source page one click away.
- Classified at intake
- Field-level extraction
- Source-retained
- Clinician-reviewed
The workflow problem
Clinical uploads quietly become a backlog.
Documents arrive faster than the team can read them. The detail that matters stays buried in PDFs and scans.
- 01
Uploads are hard to review at speed.
A PDF inbox is not a workflow. The team flips through documents to find what matters.
- 02
Important findings stay buried.
Findings live deep inside imaging reports, intake forms, and referral letters.
- 03
Documents aren't routed to the right workflow.
A panoramic radiograph and an intake form need different downstream paths — that routing is manual.
- 04
Missing chart items create risk.
When a document is missing an expected field (intake date, allergies), nothing surfaces it.
How Faurenis solves it
Read, classify, extract, flag — then route to review.
Faurenis treats every upload as a structured object: classified by type, parsed for relevant fields, checked for missing data, and presented for review with the source retained.
Upload classification
Every document is classified by type at intake (radiograph, intake form, referral, prescription, etc.).
Relevant information extraction
Fields the team cares about are extracted as structured data, linked to the source page.
Missing data prompts
Documents expected to carry a field that's absent surface as a flag, not silently as data.
Patient timeline linking
Approved documents thread into the patient timeline alongside notes and chart events.
Document summaries
A short, structured summary per document so the reviewer can scan before opening.
Review status
Clear draft → reviewed → linked states with reviewer attribution.
Searchable structured context
Extracted fields become searchable across the patient record — and the source PDF is one click away.
How it works
A six-stage pipeline with review baked in.
Extraction does not skip review. The source document is always one click away.
- 01
Upload document
Pickup from the inbox or upload surface. Source PDF is retained as the ground truth.
- 02
Faurenis classifies document type
Document is typed (radiograph, intake form, referral, etc.) with a confidence score.
- 03
Key details are extracted
Fields relevant to that document type are read into structured form, linked to source pages.
- 04
Missing or conflicting information is flagged
Expected fields that are absent or contradict prior chart data surface as flags.
- 05
Clinician or admin reviews output
Clinician-controlledA dedicated review surface compares the extraction to the source before save.
- 06
Approved summary links to chart and timeline
Approved extraction joins the patient timeline; the source PDF stays available.
Why it matters
A document inbox becomes a structured intake stream.
Illustrative shape of how the team's typical document load flows through the pipeline.
Example workflow data
Document processing pipeline per 100 uploads.
Stylised view of how the team's document load flows through the five primary processing stages.
Safety and governance
Documents are evidence. Treated accordingly.
The source document is the ground truth. Extraction is a derived layer the team can always audit back to source.
Human review
No extraction enters the chart without explicit clinician or admin review.
Source document retained
The original PDF stays available — every extracted field links back to its source page.
Extracted fields traceable
Per-field provenance — which document, which page, which extraction model version.
Audit log
Upload, classification, extraction, flag, review, link — each event logged.
Data minimisation
Only fields the team needs are extracted into structured form.
Secure file handling
Documents are stored, encrypted at rest, and access-scoped per clinic.
Built around the team
Wherever documents enter the practice.
Document Intelligence touches every role in the clinic.
For dentists
Open a patient knowing the inbound documents are already classified and the key fields are visible.
For assistants
Inbound intake forms and referrals routed to the right review queue automatically.
For practice managers
Document review backlog visible at the operating level — never silently growing.
For compliance and admin
Audit-ready per-document trail with source retention and per-field provenance.
For IT and security
Encryption at rest, access-scoped per clinic, no silent cross-tenant linking.
Continue exploring
Designed to work together.
Make documents clinically useful
Bring a real document — we'll run the full pipeline.
A 30-minute walkthrough on a real upload: classify, extract, flag, review, and link into the patient timeline.
Pilots run for 3 weeks. Designed for dental teams. AI-assisted, clinician-controlled.
Document content and extracted fields shown here are illustrative. In Faurenis, every extraction is clinician- or admin-reviewed before it links to the patient record.