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

<p id="speakable-summary" class="wp-block-paragraph">Companies working on batteries, semiconductors, and medical devices generate vast amounts of data — and much of it ends up scattered across spreadsheets and legacy systems, making it hard to use to improve products or understand failures. </p>
<p class="wp-block-paragraph">San Francisco-based startup <a href="https://www.altara.co/" target="_blank" rel="noreferrer noopener nofollow">Altara</a>, which just secured $7 million in seed funding, says it has built an AI layer designed to bridge these data gaps and bring fragmented technical information into a single platform. The round was led by Greylock, with participation from Neo, BoxGroup, Liquid 2 Ventures, and Jeff Dean.</p>
<p class="wp-block-paragraph">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.</p>
<p class="wp-block-paragraph">“Imagine if you’re a company building next-generation batteries, and a battery fails during the cell testing in the R&amp;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.”</p>
<p class="wp-block-paragraph">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.</p>
<p class="wp-block-paragraph">Altara claims that its AI dramatically slashes the time required for this process, condensing weeks of manual data triaging into minutes.</p>
<p class="wp-block-paragraph">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. “Someone pushed a change to the code, and that’s what caused an outage.”</p>
<p class="wp-block-paragraph">For instance, Greylock-backed Resolve, which is valued at <a href="https://www.prnewswire.com/news-releases/resolve-ai-announces-series-a-extension-at-a-1-5b-valuation-and-launches-resolve-ai-labs-to-advance-ai-systems-for-complex-production-environments-302743888.html" target="_blank" rel="noreferrer noopener nofollow">$1.5 billion</a>, uses AI to diagnose software failures. Altara’s vision is to act as the hardware equivalent, determining exactly what went wrong when a battery or a semiconductor fails to perform.</p>
<p class="wp-block-paragraph">Altara isn’t the only startup using AI to accelerate development in the physical sciences. Startups like <a href="https://techcrunch.com/2025/09/30/former-openai-and-deepmind-researchers-raise-whopping-300m-seed-to-automate-science/">Periodic Labs</a> and <a href="https://www.radical-ai.com/news/series-seed" target="_blank" rel="noreferrer noopener nofollow">Radical AI</a> are also tackling scientific research from the ground up. </p>
<p class="wp-block-paragraph">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.</p>
<p class="wp-block-paragraph">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.</p>