Redefining Scientific Discovery: Capgemini and Wolfram collaborate to Advance Hybrid AI and Augmented Engineering

The convergence of scientific computing and engineering is accelerating innovation in unprecedented ways.

As different sectors seek to tackle complex physical systems, optimize design and simulation, and unlock the next wave of scientific breakthroughs, Capgemini’s association with Wolfram stands as a powerful milestone. Together, we’re combining decades of expertise in symbolic computation, generative AI, and systems engineering to create what we call the Capgemini co-scientist framework—an intelligent assistant built for engineering rigor.

At the heart of this collaboration lies a shared belief: generative AI is transformative, but it must be grounded in scientific accuracy, auditability, and domain reasoning to truly serve the engineering and scientific community. To enable the robustness that scientists expect from their tools, Wolfram Language brings all the infrastructure needed for a scientific reasoning engine: unmatched breadth of symbolic computation, algorithmic modelling, and knowledge representation, resulting in a co-scientist that doesn’t just generate answers in a typical LLM way—it actually understands the problem and queries verifiable facts to produce trustworthy results.

From Natural Language to Verified Computation

What makes the co-scientist novel is its ability to go beyond text-based generation. By combining large language models with Wolfram’s symbolic reasoning capabilities and curated computational knowledgebase, users can input a natural language query and receive responses that are not only contextual but computationally synthesized.

Imagine asking co-scientist to simulate the thermal behaviour of a new material under varying conditions—or to optimize the control logic of a complex mechatronic system. Rather than simply returning a list of suggestions, the co-scientist can use real Wolfram Language code to compute precise equations, model dynamic systems, and integrate directly with engineering workflows in different environments.

Hybrid AI in Action

This collaboration brings the vision of Hybrid AI to life—an approach that blends language model fluency with symbolic reasoning, scientific simulation, and rigorous rules. It’s this hybridization that unlocks reliability and traceability in safety-critical domains such as aerospace, automotive, and industrial automation.

Hybrid AI enables iterative co-design, traceable decision-making, and seamless collaboration between AI systems and human experts. Our joint solution with Wolfram represents a concrete step toward AI systems that are not only assistive but trustworthy.

Engineering a Better Future, Together

Capgemini’s Augmented Engineering strategy is about more than just productivity—it’s about elevating human expertise through AI, enabling organizations to solve harder problems faster. Our work with Wolfram builds a bridge between natural language interfaces and the rigorous world of scientific computing, ultimately empowering engineers, researchers, and product teams to think more freely, design more confidently, and innovate more responsibly.

As this collaboration evolves, we are excited to bring the power of the co-scientist to real-world use cases—from sustainability analytics and advanced manufacturing to systems engineering and intelligent product development. This is the future of engineering: collaborative, explainable, and scientifically grounded.

Read more about the collaboration with Wolfram here