Kimia Raises $7M To Launch Its AI Knowledge Platform for the Chemical Industry
A new startup has launched an AI intelligence platform for chemical companies. Kimia, a Sydney, Australia-based software firm, has raised $7 million in seed funding for its platform designed to address gaps in institutional knowledge in the chemical industry.
Many companies’ documentation, product data, and in-house expertise are spread across internal documents and the experience of a small number of specialists. Kimia was created to make this existing knowledge accessible in real time. The platform aggregates data from sources like scientific literature, internal documentation, and supplier catalogs, then structures the data so it can be queried by commercial and technical teams. It uses AI models combined with input from domain experts to interpret chemical relationships and return answers grounded in the underlying data.
“Chemical businesses are not failing because they lack expertise. They are failing to scale it. What has been missing is a platform built specifically for the chemical industry that converts that expertise into commercial results at the speed the market demands. That is what Kimia does,” said Kimia CEO Farid Mirmohseni in a release.
Kimia co-founders Farid Mirmohseni and Sajjad Azami (Credit: Kimia)
A key feature of the platform is traceability. Each output is tied back to its original source, allowing users to verify recommendations before acting on them. The company says the system will also indicate when available evidence is insufficient to support a recommendation. Kimia says its platform has been shaped by industry veterans, chemists, formulators, and domain experts who have helped define its decision logic and evaluation criteria, guiding how the platform interprets chemical data.
Kimia’s platform is focused on commercial workflows, not just research. The system can answer technical product questions, recommend materials based on specific requirements, and support customer interactions in real time. This could ease a common bottleneck in the chemical industry where the most expertise is concentrated in R&D teams, creating dependencies for sales and support teams that need access to that knowledge.
Kimia says the platform is a tool to bridge that divide: “The chemical industry has decades of knowledge trapped in formats commercial teams cannot use. Kimia is built to unlock it and put it to work where revenue is actually won or lost: in the conversations between sellers and customers,” said Kimia CTO Sajjad Azami.
The launch comes at a time when many technical industries are exploring how to use AI to operationalize large volumes of accumulated knowledge. While general-purpose language models do well with open-ended language tasks like summarization, industrial use cases often require systems that can use structured data to produce outputs that are grounded in verifiable sources. This approach is particularly important in domains like chemistry, where small errors can lead to serious consequences.
The company notes that the recent expansion of capabilities in reasoning models has made its technology possible: “The large language model capability jump over the past two years has made it possible to build AI that actually reasons about chemical complexity, not just searches it,” the company said in a statement. “At the same time, the industry is facing a knowledge cliff: decades of formulation expertise, application knowledge, and customer context sit inside the heads of senior specialists who are approaching retirement.”
Kimia was founded by CEO Farid Mirmohseni and CTO Sajjad Azami, whose backgrounds reflect the combination of chemical domain expertise and machine learning systems design behind the platform. Mirmohseni holds a PhD in chemical engineering from the University of Sydney and has focused his research on materials science and polymer chemistry. He has experience translating technical knowledge into commercial applications, including founding a waterless car-washing company based on his research. Azami brings a complementary background in computer science and machine learning, with graduate research at the University of Victoria focused on algorithmic learning and work published at NeurIPS. At Kimia, he leads the development of the platform’s technical architecture.
Kimia’s $7 million seed round was led by Airtree Ventures, a VC firm backing Australian and New Zealand technology companies. Australian VC firms Blackbird Ventures and Skip Capital also participated in the round. The company says the fresh funds will be used to onboard new enterprise customers, deepen platform capabilities, and expand go-to-market reach across the global chemical sector.
The platform is already deployed with several enterprise customers, including adhesives firm Bostik, chemical distributor Univar Solutions, and specialty chemicals maker Stahl. According to the company, these deployments support use cases such as structuring supplier data, powering website search, and enabling faster responses from commercial teams.
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