Trace.Space Introduces Trinity, the Agent Harness to Accelerate Physical AI

A robot does not need to become sentient to hurt someone. A missed safety requirement or a software update tested incorrectly can cause real-world harm.". As AI accelerates engineering, new hardware products and prototypes are coming out 10x faster but knowing what is being built, what changed and what has actually been tested becomes a matter of physical safety. Today, Trace.Space introduces Trinity, its AI harness to scale R&D. Trinity helps hardware teams keep up with the pace AI makes possible.

Trinity expands what a single engineering team can build and manage. Specialized AI agents check requirements, analyze changes and identify gaps across hardware generations and software releases. Teams can develop the next generation of a product while continuing to improve those already in the field, carrying shared engineering work into each new variant. As the product family grows, Trinity keeps engineers in control of what each version contains, what has changed and what has been tested. Maintaining that control is a priority for Serve Robotics, a Trace.Space customer operating a fleet of autonomous sidewalk delivery robots.

"We have multiple generations of robots and multiple generations of autonomy software in the field at the same time, and each one evolves on its own timeline," said Jackie Song, Senior Systems Engineer at Serve Robotics. "The hard part isn't any single requirement - it's keeping requirements, tests, and hardware configurations connected across all of those versions at once. That's the structure we're building in Trace.Space."

The world is betting on autonomous vehicles, robots and new energy systems to solve some of humanity’s biggest problems. Most innovative companies build software-defined machines that send data back from the field and engineers put that feedback straight into R&D to build the next generation products. But too much of the engineering behind that future still runs on spreadsheets, static documents, legacy platforms not built for software-defined hardware and knowledge trapped in people’s heads. Trace.Space works with engineering teams across robotics, aerospace, automotive, and defense including Serve Robotics, Xiphos, TMAP Mobility and StandardX. 

Trace.Space was born from a problem Janis Vavere and Karlis Broders had already spent years trying to solve. Vavere saw it from the companies buying and adopting requirements-management systems at Jama Software. Broders saw it from inside the enterprises implementing them. They came to the same conclusion: the problem was not another missing feature. The foundation itself had to change.

Every complex product starts with requirements: the decisions that define what it must do, how it must perform, what rules it must meet, and how engineers will prove that it works.

Trinity keeps that definition connected to tests, design parameters, product variants, and the rest of the engineering system. Instead of creating another copy every time a company builds a new vehicle, robot, satellite, or configuration, teams define what is shared once and where each version differs. When something changes, Trinity shows what else is affected.

That same connected structure is what makes AI agents useful in engineering.

When Trace.Space launched Space Agent in February, it became the first to bring agentic AI into systems engineering. Trinity brings together three pillars the team refers to as Record, Relate, Reason.

Record the engineering truth in one place. Relate requirements, tests, parameters, and variants as the product changes. Reason across those connections to understand impact, identify gaps, and give engineers and AI agents the same system to work from.

"We built the architecture knowing AI would eventually reach the point where it could do real engineering work," said Karlis Broders, co-founder of Trace.Space. "The limiting factor was never going to be the model alone. It was whether the model had a structured, connected understanding of the product to reason over. We built that foundation first, so when the models crossed that threshold, we were ready."

More money is flowing into physical AI than at any point on record. Robotics companies raised $18.8 billion in the first half of 2026, already more than the $15 billion raised across all of 2025. Defense tech took in $14.6 billion by early June, 52 percent above its record full-year total. Space tech companies raised more than $12 billion last year, and autonomous vehicle companies have raised $21.4 billion so far this year.Turning that capital into products at scale is harder. Teams must move from a handful of prototypes to a scaled manufacturing of fleets, variants and regulated production.

"The constraint is no longer whether ambitious teams can get funded," said Vavere. "It's whether they can engineer, validate, and manufacture products fast enough to win. Until now, the infrastructure required to move with that speed and precision existed only inside a handful of the world's most advanced hardware companies, built and maintained by dedicated internal engineering teams. Trinity democratizes that capability."

Trinity is available today through Trace.Space.

About Trace.Space

Founded in 2022 in Riga, Latvia, with offices in San Francisco, Trace.Space has raised $6 million in funding from Cherry Ventures, Charlie Songhurst, Tiny, Foreword, Illusian, Fiedler Capital and Finn Murphy from Nebular, and works with engineering teams across robotics, aerospace, automotive, defense, space, and other advanced hardware industries. Trace.Space sells directly and through resell partners including Systematics in Israel and SLEXN in South Korea.