Turn claim documents into decisions, not a growing backlog.
For insurance companies running high-volume motor and health claims operations, where teams manually review claim forms, survey reports, garage invoices and medical documents before every decision.
Who it's for
Insurance companies — motor and health insurers — running high-volume claims operations where teams manually review claim forms, motor survey reports, garage invoices and medical/discharge documents before a claim can move forward.
Typically championed by
The shift
Claims teams spend a significant share of their time collecting, reading, validating and cross-referencing information across unstructured documents — claim forms, motor survey reports, garage invoices, discharge summaries — before a claim can even move forward. Formats differ by garage, hospital, surveyor and customer, so processors manually extract and reconcile the same fields case after case. The result is a repetitive, high-cost workflow, longer turnaround, and more customer follow-ups than the process should need.
Framed as an expected outcome, not a validated client metric (pre-pilot): claims teams spend less time on manual document review and cross-referencing, with more of their time going to genuine exceptions and liability decisions. Early estimates point to a 40–60% reduction in manual document-processing workload — an industry-informed estimate rather than a measured result, with validated numbers to follow real pilot deployments.
How it works
Reads and interprets four categories of claim documents — claim forms, motor survey reports, garage estimates & invoices, and medical documents — standardises the information, flags discrepancies or missing fields, runs policy and business-rule validation, and produces a confidence-scored recommendation for the claims officer. Low-confidence cases route straight to human review.
- Step 1
Evidence In
Claim forms, motor survey reports, garage estimates/invoices and medical documents (discharge summaries, bills, reports) are read directly, in whatever format they arrive.
- Step 2
AI Interpretation
Extracts and standardises key fields — customer, policy and incident details, damage descriptions, billed amounts, diagnosis and treatment — across every document.
- Step 3
Validation & Confidence Scoring
Cross-references documents against each other and against policy and business rules, then generates a confidence score for every extracted field.
- Step 4
Recommendation & Routing
A structured recommendation reaches the claims officer; low-confidence or inconsistent cases route to human review, high-confidence cases move straight to the decision queue.
Trust & governance
AI assists, humans decide
AI assists in document understanding and recommendation generation; final liability and claim approval decisions remain with human claims officers.
Every extraction is traceable
Every extraction is traceable back to the source document.
Confidence-scored, not black-box
Confidence scores indicate certainty for every extracted field.
Complete audit trail
Every AI recommendation and human action is fully auditable.
Configurable to your rules
Insurer-specific business rules and workflows are configurable, not one-size-fits-all.
Human-in-the-loop for exceptions
Exceptions and low-confidence cases always route to human review.
Enterprise-grade security
Enterprise-grade security and access controls throughout.
Document-by-document coverage
| Document Type | What the Platform Extracts & Validates |
|---|---|
| Claim Forms | Customer, policy, incident and claim details; validates mandatory fields and flags missing information. |
| Motor Survey Reports | Assessor observations, damage descriptions, recommended repairs, parts involved and severity. |
| Garage Estimates & Invoices | Repair items, labour charges, spare parts, taxes and final billed amounts — compared against survey recommendations and policy limits. |
| Medical Documents | Diagnosis, treatment, hospitalization details, dates, procedures and billed amounts from discharge summaries, bills and reports. |
You might also need
Get in touch
Frequently asked questions
Which document formats are supported?+
Claim forms, motor survey reports, garage estimates and invoices, and medical documents such as discharge summaries, bills and reports — across whatever format your garages, hospitals, surveyors and customers currently send them in.
Can the platform process handwritten or scanned claim documents?+
It reads structured and semi-structured documents, including scanned images. Handwritten content is assessed case by case since accuracy depends on legibility — we'll evaluate this directly against a sample of your own documents during a pilot.
How does the system handle missing or inconsistent information?+
Missing mandatory fields and inconsistencies across documents are flagged automatically rather than silently ignored, and routed for human review before a claim moves forward.
Can it integrate with our existing claims management system?+
Yes — DiscvrAI builds a decision and execution layer on top of your existing systems rather than replacing them, so it's designed to work alongside whatever claims management system you already run.
How are low-confidence extractions handled?+
They're routed to a claims officer for manual review, arriving with the relevant document evidence and a confidence score already attached — not silently auto-approved.
Can business rules be customized for our claim workflows?+
Yes — business rules and workflows are configurable per insurer rather than fixed.
Does AI make the final claim decision?+
No — AI assists in document understanding and recommendation generation; final liability and claim approval decisions always remain with your claims officers.
How quickly can a pilot be deployed?+
Timelines depend on your document mix and volume — talk to us with a sample of your own claim types and we'll scope a pilot plan.