AI Partnership accelerates product development

DareData, a Portuguese company specializing in the development of Artificial Intelligence solutions, and Inductiva.AI, a Portuguese startup that provides a platform for companies and engineers to run large-scale computer simulations in various industrial sectors, have announced a strategic partnership to offer an Industrial Data Science package. By combining their expertise in artificial intelligence and the generation of synthetic data through simulations, the two companies will now provide various industries with solutions capable of accelerating the development of new products by up to ten times, optimizing costs, and achieving energy savings of between 3% and 5%—all without requiring additional investment from customers.

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This solution addresses a major challenge in the industrial sector, where the design of new products requires extensive testing to assess quality and efficiency. With the solution developed by DareData and Inductiva, industrial companies can now conduct tests using synthetic data generated by computer simulations, eliminating the need for real data collection. All data processing is handled by AI, drastically reducing costs and enabling faster product development with higher quality assurance.

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“For us, this is a natural step toward meeting the needs of all sectors, including more traditional ones that have not yet adopted digitalization systems. By partnering with Inductiva, we’re combining our data expertise with their ability to run thousands of simulations, allowing us to determine the best course of action. Essentially, we’re doing Data Science without the actual data—the information comes from Inductiva’s simulations,” explains Nuno Brás, Co-Founder and Partner of DareData.

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The industrial sector faces a productivity challenge, as it heavily relies on data collection and analysis to improve performance—a factor that has slowed the widespread adoption of digitalization. However, this constraint is mitigated with the introduction of the solution now being presented.

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For example, in the pharmaceutical industry, drug production is a lengthy process, estimated to take between ten and 17 years, including the research, testing, and final decision phases. With computer simulations led by Inductiva, this process is accelerated and simplified, reducing the range of potential substances that can be used in drug creation. Partnering with DareData, recently recognized as “the fastest-growing Portuguese AI company,” the process becomes even faster thanks to the creation of synthetic data, which allows for information storage and predictive modeling using AI.

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Luís Sarmento, CEO and Co-Founder of Inductiva.AI, adds, “Even when industrial facilities are equipped with sensors to collect operational data, there’s always the limitation that the data is restricted to past scenarios, which are typically narrow in scope. By combining Inductiva and DareData’s strengths, we can predict other industrial operating scenarios through computer simulation, making the entire production process much more efficient. In the absence of real operational data, which is often the case, we use large-scale computer simulation to generate ‘synthetic data’ that serves as a starting point for training machine learning models. This solution effectively leverages AI to bring products to market more quickly, accelerating business and, consequently, the economy. At the same time, we’ve drastically reduced the likelihood of production errors by expanding the number of operational scenarios considered by AI through simulation.”

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This Industrial Data Science package is specifically designed for sectors such as Heavy Industry, Renewable Energies, Metalworking, Aeronautics, Mechanics, and Molds and Plastics. It is being developed by the Portuguese AI company, which has worked on projects for organizations such as the Heineken Group, NOS Telecommunications, and Coca-Cola, in collaboration with the Porto-based startup, which has already executed projects in fluid dynamics, molecular dynamics, structural mechanics, quantum systems, and more.

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