Scaling Broker Expertise with Agentic AI

Business Challenge

Risk placement is a high-stakes, knowledge-intensive process. Brokers are responsible for:

• Interpreting nuanced coverage needs
• Identifying suitable carriers from an expansive and ever-changing market
• Reviewing quotes, forms, and appetite guides
• Responding to clients with personalized, timely recommendations

Much of this work relies on unwritten institutional knowledge that's drawn from carrier guidelines, historical placements, underwriter preferences, and individual broker experience. This model, while powerful, is difficult to scale and creates friction in onboarding, training, and consistent service delivery.

Partnership with Stitch

To address this challenge, the broker partnered with Stitch Studio to deploy a MarketMatch Al Agent, powered by Stitch's Al Studio platform. The agent was designed to empower brokers and assist in surfacing the right carrier partners for specific risks without compromising control or compliance.

What Stitch Delivered:

• Ingested structured and unstructured sources, such as appetite guides, underwriting memos, marketing materials and broker notes.
• Created a centralized, semantically enriched knowledge base for carrier placement criteria
• Configured an explainable MarketMatch Al agent that interprets broker queries and returns tailored carrier options based on market, size, product, and historical placements.

Why it Worked

Unlike generic Al tools, Stitch's platform is an applied Al platform built for the insurance industry:

• ‍Explainable Agentic Al: Every recommendation is backed by traceable logic, citations, and structured outputs making it easy for brokers to understand and trust rationale behind each recommendation
• Human-in-the-loop Feedback: Brokers can refine agent responses and improve future outcomees through in-context rating
• Continuous Learning: New documents, updates, and market insights are automatically ingested and available for the agent to use
• Business-User Customization: Business users can update logic, add new data sources and measure and evolve agent behavior over time

What's Ahead

The agent will evolve to deliver:

• Context-aware conversations with the AI based on coverages, exclusions, industries and submission requirements
• Automated detection of appetite mismatches to reduce back-and-forth with carriers
• Data-driven decision support to surface trends in placement success and underwriter engagement

Business Impact

With StitchStudio's platform operationalized, the company achieves:

• Faster onboarding for new brokers, enabled by on-demand access to institutional knowledge
• Stronger underwriter relationships, driven by targeted, informed submissions
• Greater transparency and consistency, supporting trust in AI-powered decisions