Altara raises $7M to solve critical data challenges in physical sciences

Companies operating across industries such as batteries, semiconductors, and medical devices produce massive volumes of data. Still, much of it remains fragmented across spreadsheets and outdated systems, making it difficult to analyse, improve products, or diagnose failures.

San Francisco-based startup Altara, which recently raised $7 million in seed funding, says it has developed an AI layer that connects these disconnected data sources and unifies technical information into a single, accessible platform. The funding round was led by Greylock, with participation from Neo, BoxGroup, Liquid 2 Ventures, and Jeff Dean.

Altara was founded in 2025 by Eva Tuecke, who previously conducted particle physics research at Fermilab and worked at SpaceX, along with Catherine Yeo, a former AI engineer at Warp. The two founders met while studying computer science at Harvard University.

“Imagine if you’re a company building next-generation batteries, and a battery fails during the cell testing in the R&D process,” Yeo said. “A team of engineers has to go in and manually check a lot of different sources of data, anything from their sensor logs to their temperature data, moisture data. They cross-check historical failure reports.”

According to Yeo, scientists and engineers can spend weeks or even months navigating multiple data systems to identify the root causes of failures.

Altara says its AI platform significantly reduces that effort by consolidating and analysing data quickly, turning what would normally take weeks of manual investigation into a process that can be completed in minutes.

Corinne Riley compared Altara’s approach in the physical sciences to how site reliability engineers operate in software systems. When something breaks, “an SRE will go in, and they’ll go look at the observability stack of the company,” she explained. “Someone pushed a change to the code, and that’s what caused an outage.”

As an example, Greylock-backed Resolve, which is valued at $1.5 billion, applies AI to diagnose software failures. Altara aims to serve as the hardware equivalent, precisely identifying the causes of issues in systems such as batteries and semiconductors.

Altara is not alone in applying AI to accelerate advancements in the physical sciences. Other startups, including Periodic Labs and Radical AI, are also working on transforming scientific research and development.

However, Altara’s approach differs in that it does not attempt to replace established research or manufacturing systems. Instead, it focuses on building an intelligence layer that integrates directly with existing infrastructure, making it a more capital-efficient solution.

Riley believes that AI applications in the physical sciences represent the “next big frontier” and expects significant growth and innovation in the sector in the near future.