Albert today announced Ask Albert, agentic chemistry-native AI built for enterprise R&D, designed to surface scientific knowledge and execute research tasks with the accuracy and security enterprise chemical companies require. For decades, R&D organizations have accumulated vast scientific knowledge without a reliable way to search or act upon it. Ask Albert directly addresses this by transforming an organization’s scientific history into an intelligent system that delivers trusted answers, automates complex workflows from data analysis to formulation design, and creates immediate value for scientists without requiring years of data preparation.

Unlike generic AI bolted to R&D solutions, Ask Albert’s architecture is fundamentally built for chemistry. Powered by a custom retrieval model trained on chemistry, Ask Albert surfaces accurate information across the experiment lifecycle and executes actions on behalf of Albert OS, the company’s operating system for chemistry—all through natural language. Designed specifically for enterprise scale knowledge mining, it is already proven across companies with millions of historical documents and data points. Ask Albert maintains enterprise-grade security, permissions-aware access, and governance over how automated actions are managed and versioned across large organizations. Because it works across both structured and unstructured data, teams can start seeing meaningful value from day one.

Henkel, one of the world’s largest chemical companies, recently began using Ask Albert to surface R&D knowledge, from finding raw material alternatives to discovering past experiments to drawing connections between different projects.

Leveraging Ask Albert, Henkel is starting to break down R&D silos. Notably, the company saw more than half of the formulations surfaced to scientists originate from projects outside their own, and nearly 80% of recommended raw materials were net new to scientists receiving them. As a result, over 90% of chemists across global teams and diverse technology areas said they plan to use Ask Albert on a regular basis.

“One of the hardest problems in a large R&D organization is simply knowing what you already know. Ask Albert helped our scientists discover relevant work and raw materials they may not have found on their own. The strong engagement and positive feedback we’ve seen so far tell us we’ve only scratched the surface of what this capability can unlock across R&D,” said Houda El-Haddad, Head of Digital and Innovation Solutions at Henkel Adhesives Technologies.

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.

About Albert Invent Corp.

Albert Invent transforms how materials are invented through chemistry-native AI embedded in an operating system that captures experiments, structures data, and enables scientists to accelerate discovery. Built by chemists, Albert helps organizations turn their R&D into a strategic advantage. Albert Invent is based in Oakland, California. Discover how we’re accelerating materials science at www.albertinvent.com.

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