Exclusive: GetWhys Raises $5.2M To Help Companies Like Intel And Verizon Better Understand Their Customers

· Source: Artificial intelligence - Crunchbase News · Field: Business & Management — Entrepreneurship & Start-ups, Marketing, Branding & Advertising, Artificial Intelligence & Machine Learning · Depth: Fundamental Awareness, short

Summary

GetWhys, an AI-powered customer intelligence platform, has secured an additional $5.2 million in a "seed II" funding round, bringing its total raised to approximately $8 million. This latest financing was led by Epic Ventures, with participation from CEAS Investments, Portland Seed Fund, and existing backers Next Frontier Capital, Tuesday Capital, and Capital Eleven. The Boise, Idaho-based startup specializes in building and maintaining a proprietary library of in-depth interviews with B2B software buyers, which it then makes searchable and usable. GetWhys integrates this buyer research with AI to automate the analysis of hundreds of hours of transcripts and videos, transforming it into "go-to-market-ready" intelligence for messaging, content, and competitive materials. The platform also allows companies to connect their internal intelligence, such as sales call transcripts, and offers net-new research upon customer request. Notable customers include Intel, Verizon, Docusign, Mission Cloud, and Commvault.

Key takeaway

For Product Managers and revenue teams seeking to refine go-to-market strategies, GetWhys offers a unique approach by providing access to a continuously compounding dataset of verified B2B buyer insights. You should consider how a platform that combines human-led data collection with AI-driven analysis could accelerate your content creation, messaging, and competitive positioning, especially if your current market research is slow or costly.

Key insights

GetWhys combines human-gathered B2B buyer insights with AI analysis to create actionable go-to-market intelligence.

Principles

Method

GetWhys collects in-depth B2B buyer interviews via human researchers, then uses foundational large language models to analyze and summarize this proprietary data, turning it into go-to-market intelligence.

In practice

Topics

Best for: Product Manager, Investor, Entrepreneur, AI Product Manager

Related on AIssential

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence - Crunchbase News.