Case study 04 · Insurance technology
AI-assisted motor insurance journey
A mobile-first insurance journey that shortens onboarding and claims while keeping evidence visible to reviewers.
Interactive customer + operations prototype · Client name withheld
Challenge
Insurance onboarding and claims ask customers for details they may not know, documents they have not prepared, and evidence that teams later review by hand.
Cut customer effort without hiding the evidence, controls and review needed to issue cover or progress a claim responsibly.
System response
Customers get photo-assisted vehicle and identity capture, guided policy steps and an evidence-first claim flow. Staff get one workspace for policies, work queues, risk review, evidence, automation and feedback.
- Extraction
- Records
- Evidence
Product scope
- Photo-assisted vehicle and identity capture
- Guided quote and policy onboarding
- Step-by-step incident and evidence collection
- Document and image extraction support
- Policy, evidence, and work-queue administration
- Risk assistance with an explicit operator review layer
System architecture
Customer capture turns photos and form input into structured records.
Validation steps keep uncertain extraction visible to the user.
Policy and claim records hold the working context.
Evidence is separated from decision status for review.
The internal work queue coordinates risk and servicing actions.
Observable outcome
What the product and its repository show. These are not confidential client figures.
A shorter customer journey with evidence preserved
Consistent progression from onboarding to policy servicing and claims
AI assistance positioned as review support, not an invisible decision-maker
Repository evidence
- Interactive onboarding and claims experience
- Persisted policy, claim, and upload records
- Separate operations surfaces for evidence and risk review
Built with
- Next.js
- TypeScript
- Structured extraction
- Image-assisted onboarding
- Role-based operations UI