Building the Future of the Physical World
Ask Albert was designed for the complexity of chemistry and materials science labs, grounding every response in each organization’s data while also connecting to the world’s leading scientific databases including CAS, so scientists get complete and accurate answers in one place. Every response includes a reasoning audit trail that shows each step in its journey, such as the tools it calls and the logic behind it, allowing scientists to validate and trust the answers. Unlike many AI providers that aggregate data across customers and use cases, Albert builds trust through a different approach: zero data retention means prompts and outputs are deleted after generation, and permissions-aware access ensures scientists only see what they are cleared to see, with the ability to request access directly within the platform.
Ask Albert is useful across every part of the R&D workflow, enabling scientists to execute actions including:
• Discovery: “What EV thermal gap fillers have we tested that fit my thermal conductivity requirements, and do we still have these materials in our inventory?”
• Intelligence: “Run a regression analysis on this dataset, visualize the key trends, then generate candidate formulations using inverse design.”
• Automation: “Review the patents I uploaded to this project, compare them against my new formulations, and summarize the freedom-to-operate analysis in a new notebook page.”
“Ask Albert is fundamentally different from other AI tools being adapted for the lab,” said Nick Talken, CEO of Albert. “We’ve spent years building trust with some of the world’s leading chemistry R&D organizations, and those learnings have framed how to build AI for the enterprise: the security, governance, and scale that enterprise companies need, driving real returns on their AI investment. Instead of just a faster way to work, Ask Albert enables a foundational shift in how knowledge flows across R&D organizations and how workflows are automated.”
This launch reflects Albert’s role as a long-term AI transformation partner, guiding organizations on a journey from fragmented knowledge to a fully integrated, end-to-end R&D ecosystem. Many tools require companies to structure all data before any return on investment is realized. Uniquely, Ask Albert delivers immediate value without requiring fully structured data, but its impact grows as organizations build out their data ontology in Albert OS, helping teams recognize the value of more connected, structured data along the way. With this foundation, Ask Albert goes beyond text summaries, surfacing structured records and taking scientists directly into a formulation worksheet or raw material inventory item where all experimental details are linked.
“We are delivering the vision of agentic assistance and automation across the entire experimental lifecycle of design-execute-analyze with AI that reasons, acts, and learns from every interaction. This is just the beginning of what’s possible with chemistry-native AI that is truly designed for scientists and the real work they do every day,” said James Pycock, VP of Product at Albert.
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