Albert Raises $55M to Accelerate Chemistry-Native AI for R&D
Albert Raises $55M to Advance Chemistry-Native AI Albert has raised $55 million in Series B funding to advance artificial intelligence for scientific research. TCV led the round, attracting new investors The post Albert Raises $55M to Accelerate Chemistry-Native AI for R&D appeared first on Ventureburn .
Albert secures $55 million in Series B funding to further develop its chemistry-specific artificial intelligence platform. Venture capital firm TCV spearheaded the investment round, joined by additional backers including Delta-v Capital, Socium Ventures, High Sage Ventures, Coral Capital, Legion VC, Coatue, J.P. Morgan Growth Equity Partners, Index Ventures, and Applied Ventures.
Headquartered in Oakland, California, Albert is developing an operating system tailored for chemistry and materials science research. The company's platform merges specialized AI with enterprise security, governance, and integration features like zero data retention, granular access controls, and reasoning audit trails. Albert caters to organizations with intricate research requirements, evolving regulations, and disrupted supply chains.
Its clientele includes major players in the industry such as BASF, Henkel, Clorox, Kenvue, and Akzo Nobel. Albert's chemistry-native AI model, Valence, boasts 45 times higher accuracy than conventional AI in retrieving scientific knowledge. This enhanced accuracy stems from training on text processing and discerning function and composition, emulating the nuanced expertise of seasoned chemists.
Valence was benchmarked against formulation chemistry using Form Bench, a new metric designed to evaluate AI's performance in this specialized domain. Albert's platform, Albert OS, consolidates scientific data, AI tools, and research systems within a secure framework, empowering research teams to access institutional knowledge, analyze experiments, and expedite scientific discoveries.
Using natural language, scientists can interact with research data through Albert's Ask Albert interface, which orchestrates tools, agents, and models to facilitate intricate scientific tasks. The system aids in retrieving institutional knowledge, avoiding redundant experiments, suggesting formulation candidates, aiding experiment design, and analyzing complex datasets.
By addressing workflow bottlenecks and enhancing decision-making, Albert aims to transform enterprise research processes.
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