From vendor research to a shared market resource
How we got here
AI Market Map began with a practical problem: as enterprise AI accelerated, the number of vendors grew faster than our ability to evaluate them consistently.
A market moving at extraordinary speed
During 2024 and 2025, AI—and especially agentic AI—expanded at an extraordinary pace. While working in the FinTech sector, we watched teams across the business get pulled into a steady stream of meetings with emerging vendors.
Some companies appeared to offer the same solution under different language. Others addressed genuinely different parts of the workflow. Almost every conversation eventually became a build-or-buy decision, followed by another round of vendor evaluation.
The comparison problem
Keeping track of the market was difficult. Vendor categories overlapped, terminology changed quickly, and every presentation emphasized a different set of strengths. Comparing options apples to apples took more work than finding the options in the first place.
We started with shared Google documents and spreadsheets: lists of companies, notes from meetings, common questions, and side-by-side comparisons. Those working files made the landscape easier to navigate, but they also revealed the need for a more durable structure.
From internal process to AI Market Map
We added a formal structure for RFI and RFP work, then expanded the research beyond the vendors already in front of us. We proactively examined alternatives, adjacent products, and competitors so each evaluation could begin with a clearer view of the market.
Over time, the project outgrew the documents that started it. The result is AI Market Map: a public resource designed to organize a fast-moving vendor landscape, make company information more comparable, and help other teams approach the same build-or-buy questions with better context.
