Why We Backed Citrine: AI That Turns Materials Knowledge into Better Products
We followed Citrine for nearly a decade before investing. Its appeal is AI applied to real formulation decisions, reusable industrial knowledge and customer adoption. This March 2025 investment story has been updated with subsequent public developments through October 2026.
The investment began with a long conversation
On 21 March 2025, CM Venture Capital announced an investment in Citrine Informatics from its Evergreen Fund. We had known the company since 2016 and followed its evolution toward a software subscription model serving materials and chemicals businesses.
That history mattered. Our interest grew from understanding how the technology could fit the work of industrial customers: choosing formulations, responding to changing requirements and putting accumulated research knowledge to use.
Better products begin with better experiments
A chemical formulation must satisfy several requirements at once. A customer may want the same performance at a lower cost, a different raw material or a product adapted for another market. Each change creates a new set of trade-offs to test.
Citrine combines materials data infrastructure with AI to guide that process. Scientists define their goals and constraints, test suggested candidates and feed the results back into the model. The aim is to make each experiment more informative and preserve knowledge for the next project.
For CM, the investment case was a platform built around the decisions materials companies already need to make, with an opportunity to become part of their recurring development workflow. Explore Citrine’s approach ↗
A surfactant example makes the value tangible
In Citrine’s published Stepan case study, a customer asked for a liquid dishwashing formulation with comparable cleaning performance at a lower price. Stepan used the platform to model performance and cost, test candidate formulations and improve the model with new results.
Citrine reports that the team exceeded cleaning-performance targets after three rounds of experiments. Stepan offered the customer two formulations with different cost and performance trade-offs. The models and data could then support related projects rather than being discarded after one formulation exercise.
This is the kind of industrial use case we find compelling: a defined customer requirement, experimental validation and knowledge that can be reused. Read the public Stepan case study ↗
Connecting AI with renewable-carbon chemistry
In September 2025, Citrine and Econic Technologies announced a partnership to apply Citrine’s platform to CO₂-based polyols and surfactants. Their announcement describes models trained on formulation and experimental data to help Econic develop and optimize its products.
Both companies are in CM’s portfolio. The collaboration illustrates how an AI platform and a specialist chemistry business can address complementary parts of materials development. Read the partnership announcement ↗
How CM helps open the next conversation
CM has introduced Citrine to several Asian corporate customers, creating opportunities to discuss the platform against their materials-development needs. Our industrial network and understanding of the sector help bring the technology into conversations with potential users.
An introduction is the beginning of that work. The commercial opportunity develops as Citrine and each customer assess the fit, define a useful project and demonstrate value.
What we continue to watch
Citrine’s subsequent announcements include its June 2026 collaboration with Perstorp on alkyd emulsions and the September 2026 launch of Catalyst and Apex. These developments extend the public record of product development and industrial engagement.
We continue to focus on adoption: whether customers embed the platform in their work, reuse the knowledge it captures and extend it to further applications. That is how an AI capability can become a lasting industrial business. Follow Citrine’s public announcements ↗