Altara secures $7M to bridge the data gap that’s slowing down physical sciences

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Altara was founded in 2025 by Eva Tuecke (pictured right), who previously conducted particle physics research at Fermilab and worked at SpaceX; and Catherine Yeo (pictured left), a former AI engineer at Warp. The two met while studying computer science at Harvard University. They cross-check historical failure reports.” Scientists and engineers often spend weeks or months on this “scavenger hunt” across a multitude of data sources just to diagnose and resolve failures, she said.

Altara claims that its AI dramatically slashes the time required for this process, condensing weeks of manual data triaging into minutes. Corinne Riley, a partner at Greylock, compares what Altara is doing in the physical sciences to the role of site reliability engineers in the software world. If a system fails, “an SRE will go in, and they’ll go look at the observability stack of the company,” she said.

Altara’s vision is to act as the hardware equivalent, determining exactly what went wrong when a battery or a semiconductor fails to perform. Altara isn’t the only startup using AI to accelerate development in the physical sciences. Startups like Periodic Labs and Radical AI are also tackling scientific research from the ground up.

Altara is taking a different, much less capital-intensive approach though. Rather than trying to replace decades-old research and manufacturing firms, Altara provides an intelligence layer that plugs into their existing data. In fact, Greylock’s Riley views AI for physical science as the “next big frontier” and predicts an impending explosion of development in the sector.

Topics AI, Greylock Partners, Hardware, neo, science, Startups When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Marina Temkin Reporter, Venture Marina Temkin is a venture capital and startups reporter at TechCrunch.