Albert Invent Corp., an Oakland, California-based company that has built a chemistry-native AI operating system for research and development, announced on October 13, 2026 that it has raised US$55 million in a Series B round. The investment was led by TCV with participation from new investors Delta-v Capital, Socium Ventures, HighSage Ventures, Coral Capital, and Legion VC. Existing backers Coatue, J.P. Morgan Growth Equity Partners, Index Ventures, and Applied Ventures also joined the round.
Expanding Chemistry-Native AI for Enterprise R&D
The new capital will be used to expand Albert's chemistry-native AI capabilities, helping companies shorten development cycles and reduce time to market for everyday products. Albert was designed specifically for chemistry and materials science, combining specialized AI with enterprise security, governance, and scalability. Its platform includes zero data retention, fine grained access controls, and reasoning audit trails to meet the needs of global organizations.
Valence Model and FormBench Benchmark
Albert also announced the performance of Valence, its chemistry-native model, which new research shows is 45 times more accurate than general-purpose AI at retrieving correct answers to scientific queries. Valence was trained to discriminate chemical composition and function while reading text, much like an experienced chemist. The company also introduced FormBench, a benchmark for formulation chemistry that sets a new global standard for evaluating AI in this specialized context.
Customer Growth and Industry Adoption
Albert's technology supports research and development across large organizations, with partners such as AkzoNobel, Avient, BASF, Chemours, Clorox, Henkel, Kenvue, and Nouryon. Over the past year, project creation on Albert OS grew 26 times year over year, and the user base expanded 6 times across 44 countries. Workflow creation also rose 4 times as more teams brought different R&D processes onto the platform.
The Case for Vertical AI in Chemistry
General-purpose models consistently fail to support specialized workflows in highly sensitive industries such as legal, finance, and science. In enterprise research and development, scientists need highly specific AI capable of distinguishing between formulations, materials, processes, and experimental conditions that can look nearly identical in language but behave very differently in practice. Albert created FormBench to address this gap and establish a clearer standard for chemistry-focused AI evaluation.
Ask Albert Evolves into an R&D Partner
In six months, Ask Albert evolved from an AI search assistant to a full research and development partner that reasons across all of Albert OS. Scientists can interact with natural language, and Ask Albert orchestrates a sophisticated harness of tools, agents, and models to surface institutional knowledge and suggest formulation candidates. The system also designs experiments and runs complex data analysis to accelerate decision making.
Executive Perspectives
Nick Talken, CEO and co-founder of Albert, said enterprise AI for chemistry must be built from the ontology up because the language, data, workflows, and decisions in research and development are deeply specialized. Morgan Gerlak, Partner at TCV, noted that research and development in chemistry still runs largely on spreadsheets and institutional memory, and that Albert turns decades of lab data into faster discovery. David Lutness, Head of R&D Digital Capabilities at Kenvue, said the partnership has increased interconnectivity across a common data platform.
With the Series B funding, Albert aims to help customers build a world model of their unique science, grounded in real experimental data. The company's growth in projects, users, and workflows demonstrates increasing demand for specialized AI in the chemistry and materials science sectors. Albert's trajectory suggests that chemistry-native AI is becoming a strategic advantage for organizations seeking faster, more efficient product development.