AI Agents for Partner Onboarding in Insurance
Challenge
How a conversational, UI-driven multi-agent system helped a global insurance aggregator cut partner onboarding from 3-6 months to 2 weeks, enable multilingual self-service for carriers and brokers, and keep quality high at optimal cost through governed model selection.
How a conversational, UI-driven multi-agent system helped a global insurance aggregator cut partner onboarding from 3-6 months to 2 weeks, enable multilingual self-service for carriers and brokers, and keep quality high at optimal cost through governed model selection.
Solution
Our client, a global insurance aggregator, scales by adding new partners (carriers, MGAs, regional brokers) across dozens of countries. Each partner comes with different APIs, schemas, languages (including non-Latin scripts and right-to-left layouts), and regulatory constraints.
Historically, onboarding a single partner took 3-6 months of cross-functional effort: clarifying requirements, interpreting sparse and heterogeneous documents, writing adapter code, preparing test data, iterating through compliance checks. Multiplied by hundreds of partners, the cost ballooned and timelines stretched.
Our client, a global insurance aggregator, scales by adding new partners (carriers, MGAs, regional brokers) across dozens of countries. Each partner comes with different APIs, schemas, languages (including non-Latin scripts and right-to-left layouts), and regulatory constraints.
Historically, onboarding a single partner took 3-6 months of cross-functional effort: clarifying requirements, interpreting sparse and heterogeneous documents, writing adapter code, preparing test data, iterating through compliance checks. Multiplied by hundreds of partners, the cost ballooned and timelines stretched.
Results
We delivered a production-ready, UI-first, multi-agent system that turns partner inputs (documents, answers, samples) into working adapters and automated tests, finishing with a GitHub pull request. The solution combines a structured AI adoption process, an orchestration pipeline that thinks before it codes, and model governance from our AI Center of Excellence.
We delivered a production-ready, UI-first, multi-agent system that turns partner inputs (documents, answers, samples) into working adapters and automated tests, finishing with a GitHub pull request. The solution combines a structured AI adoption process, an orchestration pipeline that thinks before it codes, and model governance from our AI Center of Excellence.