The funding will support the scale-up of AI-driven technology designed to accelerate and improve industrial chemical manufacturing.

London: SOLVE Chemistry, an AI-driven chemistry startup, has secured 5.4 USD Million in seed funding to expand its technology platform aimed at accelerating product commercialization for pharmaceutical and agrochemical manufacturers. The company addresses a critical bottleneck in the chemicals value chain: the significant time, cost, and technical complexity involved in designing and scaling chemical production processes. These challenges frequently delay market entry for new drugs and crop protection products and increase exposure to commercial risk as market dynamics evolve during lengthy development timelines.

To overcome these constraints, SOLVE Chemistry combines proprietary ultra-high-throughput experimental hardware with advanced artificial intelligence. At its London laboratory, the company’s custom-built data-collection systems generate high-quality reaction data at speeds up to 20 times faster than conventional high-throughput experimentation methods. This accelerated data generation enables the rapid training of AI models capable of predicting optimal reaction conditions and manufacturing routes.

By integrating fast experimental feedback with predictive modeling, SOLVE Chemistry significantly reduces process development timelines, improves resource efficiency, and supports more sustainable manufacturing outcomes. The funding will be used to scale operations, enhance platform capabilities, and expand engagement with industrial partners.

According to the Chief Executive Officer of SOLVE Chemistry, "Across the different chemical industries everyone wants to be more efficient and produce the compounds society needs quicker, despite the challenges industry faces. We are helping pharmaceutical, agrochemical, and specialty chemical companies do just that.”

According to TechSci Research, AI-driven chemistry refers to the application of artificial intelligence and machine learning technologies across chemical research, process development, and manufacturing to improve speed, accuracy, and efficiency. It enables the analysis of large volumes of experimental, computational, and historical data to identify optimal reaction conditions, molecular structures, and production pathways that are difficult to uncover through conventional trial-and-error methods. AI-driven chemistry plays a critical role in accelerating innovation in pharmaceuticals, agrochemicals, and specialty chemicals by reducing research and development timelines and lowering associated costs. In process optimization and scale-up, AI supports improvements in yields, energy efficiency, and raw material utilization, contributing to more sustainable manufacturing practices. It also allows for earlier assessment of process scalability and manufacturability, helping companies reduce technical and commercial risks and adapt more effectively to changing market conditions. As advances in data availability, automation, and computing power continue, AI-driven chemistry is increasingly positioned as a strategic capability transforming chemical innovation and industrial production.