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Adam Oliner, co-founder and CEO of Graft used to run machine learning at Slack, where he helped build the companys internal artificial intelligence infrastructure. Slack lacked the resources of a company like Meta or Google, but it still had tons of data to sift through and it was his job to build something on a smaller scale to help put AI to work on the dataset.

With a small team, he could only build what he called a miniature solution in comparison to the web scale counterparts. After he and his team built it, however, he realized that it was broadly applicable and could help other smaller organizations tap into AI and machine learning without huge resources.

We built a sort of mini Graft at Slack for driving semantic search and recommendations throughout the product. And it was hugely effective And that was when we said, this is so useful, and so powerful if we can get this into the hands of most organizations, we think we could really change the way people interact with their data and interact with AI, Oliner told me.

Last year he decided to leave Slack and go out on his own and started Graft to solve the problem for many companies. He says the beauty of the solution is that it provides everything you need to get started. Its not a slice of a solution or one that requires plug-ins to complete. He says it works for companies right out of the box.

The point of Graft is to make the AI of the 1% accessible to the 99%. he said. What he means by that is giving smaller companies the ability to access and put to use modern AI, and in particular pre-trained models for certain specific tasks, something he says offers a tremendous advantage.

These are sometimes called trunk models or foundation models, a term that a group at Stanford is trying to coin. These are essentially very large pre-trained models that encode a lot of semantic and structural knowledge about a domain of data. And this is useful because you dont have to start from scratch on every new problem, he said.

The company is still a work in progress, working with beta customers to refine the solution, but expects to launch a product later this year. For now they have a team of 11 people, and Oliner says that its never too early to think about building a diverse team.

When he decided to start the company, the first person he sought out was Maria Kazandjieva, former head of engineering at Netflix. I have been working at building the rest of the founding team and also hiring others with an eye toward diversity and inclusion. So, you know, just [the other day], we were talking with recruiting communities that are focused on women and people of color, partly because we feel like investments now in building diverse team will just make it so much easier later on, he said.

As the journey begins for Graft, the company announced what it is calling a pre-seed investment of $4.5 million led by GV with help from NEA, Essence VC, Formulate Ventures and SV Angel.

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Slacks former head of machine learning wants to put AI in reach of every company - TechCrunch