Contemporary product engineering demands the creation of precise digital simulations, enabling engineers to prototype and gauge the real-world performance of materials. While traditional software platforms such as those from IBM and Dassault are commonly used, an influx of startups now emerge, propelled by generative AI technologies.
One notable example is Trace.Space, hailing from Riga, Latvia. This AI-enhanced platform is specifically crafted to assist engineers in the development of industrial products.
As Western manufacturing faces significant challenges in competing with its rapidly advancing Asian rivals, the urgency to develop these platforms for expedited product development is palpable. Recently, we witnessed the launch of Luminary, along with Dessia Technologies, which also offers an AI-driven platform to streamline engineering processes.
Trace.Space is particularly tailored for developing electric vehicles, autonomous systems, satellites, robotics, semiconductors, and medical equipment. Unlike traditional solutions that are ‘on-premise’, Trace.Space employs a modern cloud computing model. This platform also facilitates collaboration between manufacturers and suppliers on joint product specifications, thereby minimizing response times.
Janis Vavere, the co-founder and CEO of Trace.Space, remarked to TechCrunch: “Every organization worldwide engaged in producing complex regulated products—such as automotive, medical, or aerospace industries—confronts the challenge of increasing complexity in design. Legacy tools and processes are struggling to keep pace. IBM’s tools were developed in the late 1980s and are restricted to desktop clients that require installation on individual machines.”
Having previously worked at Jama Software, a more contemporary design platform, he recognized the urgency for a cloud-based, AI-driven methodology: “Now is the perfect time to merge modern software architectures and user interfaces with AI in these sectors. Companies are actively seeking superior solutions.”
Trace.Space goes beyond being a simple ‘AI wrapper’; Vavere explained: “We utilize AI models like Llama, deterministic AI libraries, and elements of OpenAI’s LLM.”
In addition to his role at Jama Software, where Vavere was formerly a sales leader, he dedicated two years to leading sales at the translation management software firm Lokalise. Co-founder Mikus Krams also comes from Lokalise, where he worked in operations, while the third co-founder, Karlis Broders, had prior experience implementing Jama and Polarion in large-scale initiatives.
Trace.Space has successfully secured $4 million in seed funding, with Cherry Ventures taking the lead, alongside Riga-based Outlast Fund and previous investors Nebular, Fiedler, and Change Ventures.
Compiled by Techarena.au.
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