5 Go-to-Market Lessons from Building an AI Governance Platform During the LLM Boom

Discover key go-to-market insights from Breeze ML’s journey in AI governance, including how to navigate emerging markets, time market entry, and build for enterprise sales.

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5 Go-to-Market Lessons from Building an AI Governance Platform During the LLM Boom

5 Go-to-Market Lessons from Building an AI Governance Platform During the LLM Boom

When ChatGPT launched in late 2022, countless startups rushed to build the next great language model. But in a recent episode of Category Visionaries, Breeze ML founder Harry Xu revealed a different playbook: while others chased the LLM gold rush, his team focused on the unsexy but crucial infrastructure of AI governance. Their journey offers valuable lessons for founders navigating emerging markets.

  1. The Power of Swimming Against the Current

The most profitable opportunities often lie in the opposite direction of the crowd. “As everybody was all in for LLMs, we kind of backed out,” Harry explains. Instead of joining the AI model race, Breeze ML identified a fundamental need that would affect every AI company: governance and compliance.

This contrarian bet wasn’t based on gut feeling. It came from extensive customer discovery: “I just talked to a lot of people. I had tons of conversations with people doing different things in different roles… data scientists… machine learning engineers… VP of engineering… compliance officers… CTOs, CEOs.”

  1. Build for Inevitable Market Forces

Sometimes the best GTM strategy is to position yourself ahead of regulatory requirements. Harry recognized that AI governance wasn’t optional: “The EU AI act is already there, and then they’re looking to finalize the law by the end of this year, and then that’s going to come into effect in the year of 2025.”

The consequences of ignoring these requirements are severe: “We’re talking about like a huge fine, something like 6% of your annual global revenue, like uncapped.” This creates built-in demand – companies won’t have a choice about whether to implement governance solutions.

  1. Find Your Beachhead Markets

While AI governance will eventually affect every company using AI, some sectors face immediate pressure. Harry identified these early adopters: “Healthcare is the industry that is facing regulations from FDA… The banks are facing very strict regulations and compliance from SEC.”

These regulated industries provide natural entry points, allowing Breeze ML to establish its platform before expanding to broader markets. It’s a classic example of finding the customers who need your solution most urgently.

  1. Navigate Undefined Markets

Building in an emerging category requires a different playbook. As Harry notes, “People don’t know what to do yet… people in this market don’t know what to do at this point. And there are no existing tools.” Even the experts are still figuring it out: “We talked to a lot of lawyers and privacy attorneys… everybody was talking about auditing AI, auditing models. But in terms of concrete steps, the action items, nobody had a good idea of what to audit.”

This ambiguity creates both challenges and opportunities. While it makes the sales cycle longer, it also means early movers can help define the category itself.

  1. Prepare Thoroughly Before Fundraising

One of Harry’s key lessons involves timing and preparation: “If I start the signal one more time… I will start paving the road a year before we see the investors, including, for example, assemble the team, clear out the potential IP issues, do the customer survey and then get MVP build.”

This becomes even more crucial when building in an emerging category where investors might not have established frameworks for evaluating opportunities.

Building for the Long Game

Breeze ML’s approach to category creation offers a masterclass in strategic patience. Rather than chasing immediate market excitement, they’re building infrastructure for long-term market requirements. Their vision is clear: “We’ll be the leading platform in AI governance for both the US and EU market.”

For founders building in emerging markets, the lesson is clear: sometimes the biggest opportunities lie not in the technology everyone’s talking about, but in making that technology viable at scale. It requires looking past the hype cycle to identify fundamental market needs – even if those needs aren’t yet fully articulated.

This methodical approach to market development, combined with careful timing and thorough preparation, provides a valuable template for founders building in undefined spaces. While it might not generate immediate buzz like the latest AI model, it positions you to capture value as the market matures.

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