Altara received $7 million to close the data gap that is slowing down physical science

Companies in batteries, semiconductors, and medical devices generate huge amounts of data — and most of it ends up scattered across spreadsheets and legacy systems, making it difficult to use it to improve products or understand failures.

San Francisco-based startup Altara, which just received $7 million in seed funding, says it has built an AI layer designed to bridge these data gaps and bring together 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 Tuecki (pictured right), who previously conducted particle physics research at Fermilab and worked at SpaceX; and Katherine Yu (pictured left), former AI engineer at Warp. The two met while studying computer science at Harvard.

“Imagine you are a company building next-generation batteries, and the battery malfunctions while testing the cells in the R&D process,” Yu said. “A team of engineers have to go in and manually check a lot of different data sources, anything from their sensor logs to temperature data and humidity data. They also review historical crash reports.”

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

Altara claims that its AI dramatically reduces the time needed for this process, condensing weeks of manual data sorting into minutes.

Corinne Riley, partner at Greylock, compares what Altara does in the physical sciences to the role of site reliability engineers in the software world. If the system fails, “the SRE will come in, and they’ll go look at the company’s monitoring toolkit,” she said. “Someone made a change to the code, and that’s what caused the outage.”

For example, Greylock-backed Resolve, which is valued at $1.5 billion, uses artificial intelligence to diagnose software faults. Altara’s vision is to act as a hardware equivalent, identifying exactly what went wrong when a battery or semiconductor failed to perform.

Altara isn’t the only startup using AI to accelerate development in the physical sciences. Startups like Journal Labs and Radical AI are also dealing with scientific research from the ground up.

Altara, though, takes a different, less capital-intensive approach. Rather than trying to replace decades-old research and manufacturing companies, Altara provides an intelligence layer that plugs into its existing data.

In fact, Greylock’s Reilly views AI in the physical sciences as “the next big frontier” and predicts an imminent explosion in development in the sector.