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Oakland's Albert closed a $55M Series B led by TCV to build its chemistry-native AI operating system for R&D, with valuation undisclosed.
Key Takeaways
- Albert raised a $55M Series B led by TCV, announced October 13, 2026.
- Coatue, J.P. Morgan Growth Equity Partners, Index Ventures and Applied Ventures returned; five new investors joined.
- Valuation and total capital raised were not disclosed.
Lead
Albert, the Oakland, California company also known as Albert Invent, announced a $55 million Series B on October 13, 2026. TCV led the round. The money will go toward expanding the company's chemistry-native AI capabilities for manufacturers and research organizations that formulate paints, adhesives, cleaning products and other materials.
The company did not disclose its valuation. It also did not state a total raised to date, though earlier disclosures put its funding above $45 million before this round.
Who Else Is in the Round?
Five new investors joined: 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 participated.
TCV is not a stranger to the cap table. It took part in the $22.5 million Series A in December 2024, which Coatue led. Moving from participant to lead in under two years, with the Series A lead still in the round, is a conventional signal of insider conviction rather than a rescue or a reset. Albert also took a growth investment led by J.P. Morgan Private Capital in February 2025, so the Series B is the third institutional round in under two years.
What Does Albert Actually Sell?
Albert sells software that replaces the paper notebooks and spreadsheets where most formulation work is still recorded. Scientists use it to log experiments, build new formulas and query their own experimental data in natural language through a feature called Ask Albert.
The company's pitch rests on Valence, its chemistry-specific model. Albert says Valence is 45 times more accurate than general-purpose AI at retrieving correct answers to scientific queries. It built a benchmark for the task, FormBench, which it describes as a new standard for evaluating AI in formulation chemistry.
That claim comes with a caveat. The benchmark was created by the company whose product tops it, and Albert has not named an independent party that validated the 45x figure.
How Fast Is the Platform Growing?
Over the past year, project creation on the platform grew 26 times, and workflow creation rose fourfold. The number of scientists using it grew sixfold across 44 countries. Those are usage figures, not revenue; Albert did not disclose revenue, contract values or customer counts.
Named customers include BASF, Henkel, Clorox, Kenvue, AkzoNobel, Avient, Chemours and Nouryon. Most are large, slow-moving industrial buyers, which supports the case for sticky enterprise contracts but also means long sales cycles.
Why Does the Founder's Background Matter?
CEO and co-founder Nick Talken previously ran digital R&D at German chemical group Henkel, one of Albert's customers. He co-founded the company in 2022 after watching duplicate work pile up in that role. He has said roughly 30% of scientific experiments are duplicative, because results sit in formats that make them hard to find later.
That figure is the founder's estimate, not an audited industry statistic. Still, the problem it describes is the same one that gives a records-first product its wedge: before a model can suggest a formula, someone has to digitize the history of what has already been tried.
What Does the Round Imply?
The round implies that investors see formulation chemistry as a vertical where domain-specific data outweighs the general models from large AI labs. Albert's argument is that a model trained and evaluated on chemistry beats a frontier model asked to guess. That is plausible, but it depends on whether customers keep feeding proprietary data into a third-party system and whether the labs close the gap with fine-tuning.
Competition comes from several directions. Established lab-informatics vendors are adding AI features. Frontier model providers are courting the same enterprise R&D budgets. Albert's defense is the installed workflow: once a company's experiments live in the platform, switching costs rise.
Outlook
Albert enters its next phase with fresh capital from its largest investors, a customer list weighted toward global chemical manufacturers, and usage growth that is steep but undisclosed in dollar terms. The next test is whether the 45x accuracy claim holds up outside a self-built benchmark, and whether usage converts into reported revenue. With no valuation disclosed, the round's price will stay unknown until a later filing or financing reveals it.
