Insurance
API Design & Integration for Insurance
API Design & Integration for insurance, built around the constraint that defines the sector: claims decisions need an audit trail and a consistent basis across assessors.
- Regulations in scope
- 3
- Systems we integrate
- 4
- Typical first release
- 6 weeks
What changes when it is insurance
Orqent Labs designs APIs that partner teams can integrate without a support call, with a sandbox and generated docs from day one.
In insurance, claims decisions need an audit trail and a consistent basis across assessors. That single fact reshapes how api design & integration has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.
The workload we are most often asked to take on first is policy servicing requests, usually integrated against CRM. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.
Built by engineers who ship production systems, not by a practice that subcontracts the build. We hand over with runbooks, tests and a team that knows how it works, not a dependency.
The sector constraints we design around
- Defining constraint
- claims decisions need an audit trail and a consistent basis across assessors
- Regulations in scope
- IRDAI regulations · DPDP Act 2023 · grievance redressal timelines
- Systems of record
- policy administration · claims management · CRM · actuarial platforms
- Where we usually start
- claims document intake and validation
API Design & Integration workloads in insurance
- claims document intake and validation
- underwriting file assembly
- fraud triage
- policy servicing requests
- renewal outreach
What is included
- OpenAPI specification written before the implementation
- Versioning strategy that does not break consumers
- Authentication, scopes and rate limiting
- Webhooks with retries and signature verification
- Idempotency on every state-changing endpoint
- Generated documentation and a sandbox
Questions from this sector
Can AI decide claims?
It can decide straightforward low-value claims within defined rules, and should assemble and recommend on everything else with a human deciding. The split is a policy decision you set, not one we make.
How much can claims cycle time improve?
Document intake and validation are usually the bottleneck, and automating them typically removes days. We baseline your current cycle before promising a figure.
REST or GraphQL?
REST for partner-facing and public APIs where caching and simplicity matter; GraphQL where a first-party client needs flexible, varied queries. Most systems end up with both, used deliberately.
Do you document it?
Generated from the OpenAPI specification, with a working sandbox. Documentation written by hand and separately always drifts.
Can you integrate with legacy SOAP systems?
Yes, usually by wrapping them in a clean modern interface rather than exposing the legacy contract onward.
Other capabilities for insurance
- AI Agent Development for Insurance
- Agentic Workflow Automation for Insurance
- LLM Application Development for Insurance
- RAG & Knowledge Retrieval for Insurance
- Chatbot Development for Insurance
- WhatsApp Bot Development for Insurance
- Voice AI Agents for Insurance
- Document Processing & IDP for Insurance
- AI Copilot Development for Insurance
- Predictive Analytics & Forecasting for Insurance
API Design & Integration for insurance, worth a conversation?
Tell us the workload and the regulation it sits under. We will tell you what is realistic.
Or email bd@dtrasglobal.com · call +91 74118 77878