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Home » Altara sets aside $7 million to close data gaps slowing down physical sciences
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Altara sets aside $7 million to close data gaps slowing down physical sciences

adminBy adminMay 6, 2026No Comments3 Mins Read
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Companies working in batteries, semiconductors, and medical devices generate vast amounts of data, much of which ends up scattered in spreadsheets and legacy systems, making it difficult to use to improve products or understand failures.

San Francisco-based startup Altara, which just secured $7 million in seed funding, says it has built an AI layer designed to bridge these data gaps and unify fragmented technical information into a single platform. The round was led by Greylock with participation from Neo, BoxGroup, Liquid 2 Ventures, and Jeff Dean.

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.

“Imagine you’re a company manufacturing next-generation batteries and your battery fails during cell testing during your research and development process,” Yeo says. “Teams of engineers have to manually check various data sources, from sensor logs to temperature data to humidity data. They cross-check historical failure reports.”

Scientists and engineers often spend weeks or months on this “scavenger hunt” across numerous data sources just to diagnose and resolve failures, she said.

Altara claims that AI has significantly reduced the time required for this process, condensing weeks of manual data triage into minutes.

Corinne Riley, a partner at Greylock, compares what Altara is doing in the physical sciences to the role of a site reliability engineer in the software world. If a system fails, “the SRE comes in and goes looking at the company’s observability stack,” she said. “Someone pushed a code change that caused an outage.”

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For example, Greylock-backed Resolve is valued at $1.5 billion and uses AI to diagnose software failures. Altara’s vision is to act as a hardware equivalent, determining exactly what went wrong when a battery or semiconductor fails.

Altara is not 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.

However, Altara takes a different approach that is much less capital intensive. Rather than trying to replace decades-old research and manufacturing companies, Altara provides an intelligence layer that builds on existing data.

In fact, Greylock’s Riley sees AI for the physical sciences as “the next big frontier” and predicts an imminent explosion of development in this area.

If you buy through links in our articles, we may earn a small commission. This does not affect editorial independence.



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