AI for Insurance
Policy knowledge to tested claims workflows.
How Prakura could support insurance teams — from today's challenges to a governed AI journey.
Claim decisions stay with qualified people.
1 · Industry challenge
What insurance teams tell us
- Requirements turn into test cases by hand
- Policy wording questions slow service teams
- Release readiness is unclear
2 · AI opportunity
- AI BA and QA agents turn requirements into scenarios
- Grounded policy-wording answers
- Visible release readiness
3 · Prakura solution
What Prakura brings
- Policy knowledge
- Claim-document assistance
- QA automation
- Customer service
- Requirements/test generation
- Workflow intelligence
- Quicker policy answers
- Better claim document handling
- Higher test coverage
Benefit categories, not measured results.
4 · Real-work animation
Requirement to release
Press play to watch the workflow. The highlighted step is where a person reviews or decides.
- Requirement
- Business Analyst Agent
- Test Scenarios
- QA Agent
- Automation
- Release Readiness
Before vs after
QA, traditional vs AI-assisted
Traditional
- Requirement
- Manual Test Design
- Manual Regression
- Slow Failure Investigation
AI Assisted
- Requirement
- QA Agent Suggestions
- Human Review
- Automated Coverage
- Failure Intelligence
6 · Architecture
How it fits together
- 1Product, QA and service teams
- 2BA → QA agent hand-off
- 3Automation framework
- 4Release dashboard
7 · Trust
Boundaries we design in
- Claim decisions stay with qualified people
- Scenarios reviewed before automation
- Audit of every agent suggestion
8 · See Prakura for Insurance
We tailor the demo to your industry, audience and priorities.