Revolutionizing Product Engineering with Generative AI

The modern product engineering landscape requires the creation of highly accurate digital simulations, enabling engineers to design prototypes and understand the real-world performance of materials. Currently, legacy software platforms from companies like IBM and Dassault dominate the market, but startups are now joining the fray, powered by generative AI.

One such startup is Trace.Space, hailing from Riga, Latvia. This AI-driven platform has been designed specifically for engineers to develop industrial products, catering to the needs of various industries such as electric and autonomous vehicles, satellites, robots, semiconductors, and medical devices.

With Western manufacturing facing intense competition from its Asian counterparts, the pressure to develop innovative platforms is mounting. Recent examples include the emergence of Luminary and Dessia Technologies, which also utilize AI to automate engineering processes.

Trace.Space takes a modern, cloud computing approach, allowing manufacturers and suppliers to collaborate on shared product requirements, thereby reducing response times. This approach is a significant departure from traditional ‘on premise’ solutions.

Janis Vavere, co-Founder and CEO of Trace.Space, shared his vision with TechCrunch: “Every company in the world that builds complex regulated products in automotive, medical, aerospace, and so on, faces the issue that these products are becoming increasingly complex, especially to design. The legacy tools and processes are struggling. IBM’s tools for this were designed in the late 80s. It’s a desktop client and needs to be installed on every computer.”

After working on Jama Software, a more modern design platform, Vavere realized the need for a cloud-based, AI-driven approach: “It’s now the right moment to combine modern software architectures and UIs with AI, and apply them to these industries. Companies are looking for something better right now.”

Trace.Space is not simply an ‘AI wrapper’; it utilizes AI models like Llama and deterministic AI libraries, as well as aspects of OpenAI’s LLM.

The founding team of Trace.Space boasts a diverse background. Janis Vavere was previously a sales leader at Jama Software, while Mikus Krams, co-founder, worked in operations at Lokalise and the software development startup Chili Piper. Karlis Broders, the third co-founder, had previously implemented Jama and Polarion in large-scale projects.

Trace.Space has secured $4 million in seed funding, with Cherry Ventures leading the round, joined by Riga-based Outlast Fund, along with earlier investors Nebular, Fiedler, and Change Ventures.