The Right Data Not More

With the news of DeepSeek & the markets going volatile for anything AI-related, there has been more and more talk about what fuels AI-- Data. I have been saying for a while it’s not just access to lots of data, but having the right data is most important. If we believe AI & LLMs are being democratized and are a race to the bottom, then the applications of AI along with the right data & data moats are what’s most important.

I think of this in a similar way to thinking about vertical SaaS companies- having a deeper understanding of use cases, workflows, and real problems, combined with niche, specialized, focused datasets is a powerful way to build a company. One of the reasons I always thought IHS was a great acquisition by Markit, or why Informa Intelligence was an undervalued asset or why GlobalData’s focus on niche acquisitions is smart or why the private company AggregateIntelligence is so interesting is because they focus on niche, verticalized datasets. Data just on the storage unit industry or focused deeply on the hospitality industry or on rental cars. Niche, focused, deep insights on specific verticals have lots of use cases and are where I think the AI applications win.

Investing in LLMs is a game being played by 0.1% of investors, but finding the next best AI applications is where I think we will see some real innovation. Creating unique, industry-specific data or acquiring unique data moats is what going to supercharge these next winners.

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