Overview
Organizations in the insurance industry often struggle with fragmented firmographic data spread across multiple internal systems and third-party sources. These inconsistencies lead to duplicate records, incomplete profiles, and delayed decision-making across sales, marketing, and operations. In this webinar, we will explore how a leading insurance provider unified firmographic intelligence using Matchbook AI on AWS to create a single, trusted view of business entities. Attendees will learn how firmographic unification improves operational efficiency, enables better segmentation, and supports data-driven decision-making across the enterprise. Through a real-world case study, we will walk through the challenges, solution architecture, and practical lessons learned—providing a clear blueprint for teams looking to modernize their firmographic data strategy.
Why You Should Attend
- Learn how to eliminate fragmented firmographic data
- Understand how unified data improves decision-making and operational efficiency
- Gain practical insights from leaders with deep enterprise data and GTM experience
- Real-world insurance industry case study with solution architecture
Featured Speakers
Founder & CEO
Matchbook AI
Rushabh Mehta is the Founder and CEO of Matchbook AI. He brings deep experience from his past roles at Raymond James, Microsoft, and the US Department of Defense. Rushabh was also a Global Platform Architect for the underlying integration platform for the Microsoft Azure Cloud, where he worked on large-scale data and integration initiatives. His expertise spans enterprise data platforms, cloud architecture, and building scalable data-driven solutions.
Co-Founder & CGO
Matchbook AI
Brian Mac Mahon is a seasoned venture capitalist and go-to-market specialist. Over the past decade, he has invested in and helped build branding and growth strategies for more than 300 companies. As Co-Founder and CGO, Brian brings deep expertise in scaling businesses, positioning technology platforms, and driving market adoption.
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