Ep 287: Kyle Geoghan, Co-Founder & CEO, Indemn

In this episode of the FNO: InsureTech Podcast, we welcome Kyle Geoghan, Co-Founder and CEO of Indemn, for a deep discussion on the real-world impact of generative AI in insurance. Kyle shares his trajectory from early days in a family insurance agency, through his experience at CoverWallet, to launching Indemn in 2021. The episode details how Indemn began by building an MGA for event insurance with Markel—where nearly 95% of its direct-to-consumer operations rely on AI agents—and how the firm is now focusing primarily on its core SaaS platform. Listeners gain a data-driven understanding of how Indemn’s technology automates quoting, underwriting, broker support, and especially broker portal workflows, as well as Kyle’s evidence-based view of industry adoption.

Key Highlights

• Kyle traces his roots to his family’s Long Island insurance agency, starting at age 12 and later moving to digital innovation at CoverWallet before co-founding Indemn.
• Indemn was launched in 2021 as a generative AI company for insurance. It initially operated as an MGA selling Markel-backed event and wedding insurance, introducing an AI agent model—at EventGuard, approximately 95% of customer interactions are handled by AI agents.
• As part of a strategic pivot, Indemn is selling the EventGuard MGA subsidiary to devote greater resources to SaaS technology enablement for carriers, MGAs, and broker networks.
• Indemn’s platform supports AI-driven quoting, stepwise underwriting, certificate generation, and status updates. Broker portal assistance is a core use case, enabling agents to receive accurate, real-time answers to underwriting and product questions, reducing repetitive workload by 30–40% for underwriters and CSRs.
• Adoption patterns show most consumer users are comfortable with AI workflows, while a majority of brokers also warm to this model over time—particularly when embedded in broker portals with feedback mechanisms for user trust.
• Kyle notes that, historically, insurance industry adoption has been cautious; however, he identifies late 2022 and 2025 as crucial milestones, with 2025 predicted as a year of significant scaling in generative AI deployment across the sector.