Synera raises $40M to embed agentic AI in engineering workflows at NASA and BMW

German startup Synera has raised $40M in a Series B round to put agentic AI not into showcase demos but into the real engineering processes of large industrial companies: the places where teams calculate loads, run simulations, approve designs and answer technical requests.

The Bremen-based company builds a platform for industrial engineering that does not try to replace existing software but links it into a single orchestration layer. Synera says its system already works with more than 75 engineering tools, including products from Altair, Autodesk, Hexagon, PTC and Siemens. On top of that layer run teams of AI agents that can carry out whole chains of tasks on their own: from design and simulation to optimization, cost estimation and reporting.

This is the key point for the industry: companies are not asked to tear out their current infrastructure for AI, but to build AI directly into the processes they already have. Against that backdrop, it stands out that Synera names NASA, BMW, Airbus, Volvo Trucks and Hyundai among its current deployments.

The round was led by Revaia, and Capgemini joined the deal through its ISAI Cap Venture. All Series A investors also returned: UVC Partners, BMW iVentures, Cherry Ventures, Venture Stars and Spark Capital. For Synera this is not just money but a vote of confidence from funds that have already seen the company at work.

The new capital will go toward faster growth in the US and international markets. The company already has a presence in Boston, and Capgemini's participation looks strategically important also because it is one of the world's largest providers of IT and engineering services to the automotive and aerospace sectors. After this round, Synera's total funding has grown to roughly $58M.

Synera is betting on agentic AI as an autonomous execution layer inside engineering workflows. According to the company, such agents can run iterative simulations, compile reports, respond to RFQs and move tasks through approval stages without constant manual involvement at every step.

The deployment model matters too: the platform runs on-premises, so engineering intellectual property and sensitive data stay within the customer's own infrastructure. For companies working with CAD models, simulation results, part requirements and manufacturing constraints, this is often a mandatory condition. In practice, Synera is trying to solve not the problem of a convenient chat for engineers, but the problem of giving AI access to the systems where real engineering work already happens.

So far the story looks stronger than the typical AI pitch because of concrete results. According to the company and validation by Frost & Sullivan, using the platform cut finite element modeling time by 95% at the EDAG engineering group. At BMW's Additive Manufacturing Campus, Synera helped reduce the mass of a 3D-printed robotic gripper by 30%. Another telling example is NASA, where several agents turn requirements into verified part designs and run hundreds of design iterations in one hour.

All of this sits against a broader market backdrop: according to Gartner, manufacturers plan to increase investment in generative AI, but only some prototypes reach production. Synera builds its thesis on the idea that the industry's main problem is not the quality of model answers but weak integration of AI with existing engineering infrastructure.

For the market this is an important marker: the next stage of agentic AI adoption in industry will depend not on loud promises but on companies' ability to embed agents in complex, error-sensitive processes with strict data security requirements. If Synera can scale its experience with customers of the caliber of NASA, BMW and Airbus, it has a chance to become one of the notable players that turn agentic AI from an experimental add-on into a normal working layer of engineering infrastructure.