Albert Invent Raises $55M Series B for Chemistry-Native AI

Ken Kisner grew up in a paint factory, a useful education for somebody who would eventually help turn laboratory work into software. At Albert Invent, that industrial experience sits behind a question with immediate commercial consequences: how much of a company's earlier science can its next scientist actually use?

The Oakland, California company announced a $55M Series B led by TCV on October 13, 2026. Albert will use the investment to expand its chemistry-native AI capabilities, giving enterprise research teams more ways to retrieve knowledge, analyze experiments and develop new materials within Albert OS.

The investment reaches a business whose work spans internal laboratories and the relationship between chemical suppliers and customers. That makes Albert an instructive example of vertical AI: the software's usefulness depends on understanding how a particular industry records its work, shares its knowledge and decides what to try next.

TCV backs a company built from chemical-industry experience

TCV leads the round alongside new participating investors Delta-v Capital, Socium Ventures, HighSage Ventures, Coral Capital and Legion VC. Returning investors include Coatue, J.P. Morgan Growth Equity Partners, Index Ventures and Applied Ventures, LLC. The announcement identifies expansion of Albert's chemistry-native AI as the use of proceeds, without publishing a detailed allocation or a new valuation.

Index Ventures lists Nick Talken, Ken Kisner, Neelesh Vaikhary and Zack Kisner as Albert's founders. Albert's current leadership page identifies Nick Talken as CEO, Ken Kisner as board chairman and Zack Kisner as Chief Work Officer. Those present roles matter because a founding story and an operating organization can develop in different directions.

Talken and Ken Kisner previously built Molecule, which Henkel acquired in 2019. F-Prime's account of Albert's $7.5M Seed round connects the founders' industry experience with the disconnected tools and lost experimental data they sought to address. Albert's independent company dates to 2022; its internal software history goes back further.

The new Series B also follows a $20M growth investment announced in February 2025. Deal counsel Fenwick identifies J.P. Morgan Private Capital's Growth Equity Partners as that round's lead, with Coatue and TCV participating. The financing history shows several institutions continuing their relationship with a company already working inside enterprise R&D.

Chemistry AI needs the conditions around an experiment

A formulation carries a record of decisions: which materials were used, in what proportions and under which experimental conditions. When another team needs to adapt a product, that record can narrow its search for a useful starting point. A notebook entry becomes much more valuable when a scientist elsewhere can understand why it belongs to the problem at hand.

Albert OS is designed to connect projects, materials and experiments in a structured record. Its chemistry-specific models include Valence for retrieval and Breakthrough for predicting and ranking candidate formulations. Ask Albert brings natural-language questions and actions into the operating system, including searching prior work, analyzing data and helping plan experiments.

These tasks connect information retrieval to a physical decision. A candidate formulation still has to face the experiment a chemist chooses to run, with the performance targets and practical constraints that accompany it. Albert's proposition is that the software can give that decision a better starting record and make the administrative work around it easier to perform.

Albert also announced FormBench, a benchmark for formulation chemistry, alongside its financing. Scientific retrieval requires careful treatment of composition, function and experimental context, so evaluation belongs close to the domain itself. Buyers examining a chemistry model should ask which tasks were measured and how those tasks compare with their own laboratory work.

For a chemical manufacturer, replacing an ingredient can bring procurement, product performance and research into the same conversation. An AI tool enters that conversation with greater responsibility when its suggestions draw on the organization's accumulated experiments. The history behind a recommendation needs to remain legible to the people deciding whether to test it.

Customers give the platform different kinds of work

Albert's AkzoNobel partnership, announced in July 2026, supports the paint manufacturer's Digital Workbench initiative. AkzoNobel describes an R&D organization with more than 2,000 professionals working across 70 labs in over 20 countries. Connecting that network makes collaboration and consistent experimental records part of the deployment itself.

The joint announcement also emphasizes change management. A shared platform has to become something people use while conducting their research, rather than another place they update after the useful work is finished. That is an organizational assignment for managers and scientists as well as a technical assignment for the software provider.

A different relationship appears at Nouryon's BeautyCreations. Nouryon announced the Albert-powered tool in April 2025, allowing personal care formulators to describe their requirements and search its formulation knowledge through natural language. Nouryon says the example formulations are screened for intellectual-property concerns and do not contain customer proprietary information.

Here, the knowledge reaches beyond the supplier's own laboratory. A customer choosing ingredients can explore how they might fit a product brief, with the supplier's existing formulation expertise helping make the introduction useful. Albert therefore has work to do both where experiments are recorded and where chemical knowledge helps a customer decide what to develop.

The Series B expands an operating relationship

Albert reports that project creation grew 26x and its scientist user base grew 6x over the past year, with users spanning 44 countries. These are company-reported adoption measures, presented without absolute baselines or corresponding revenue figures. They describe expanding activity on the platform while leaving the commercial scale of that activity undisclosed.

The operating challenge grows with the network. Different laboratories can contribute years of useful work while naming materials, describing processes and recording conditions in different ways. Making those histories reusable asks Albert and its customers to develop a common scientific record without losing the distinctions that made each experiment meaningful.

TCV's investment finances that work at a company with established chemical-industry relationships and a broader AI agenda. DevCuration's coverage of physics AI at Flexcompute offers a related view of specialized software entering industrial engineering. For R&D leaders evaluating Albert, the relevant discussion extends from model capability into deployment, ownership of experimental information and the habits that let teams learn across sites.

At AkzoNobel, that work continues through the Digital Workbench rollout. At Nouryon, it reaches the formulator describing a desired product and looking for an ingredient that fits. Albert's new capital follows those conversations back into the scientific record, where the next experiment can add something another team will eventually need.