Simulation Testing Platform by Trace Machina Aims to Update Safety-Critical Applications

When a malfunctioning CrowdStrike update disrupted critical infrastructure such as airports, 911 call centers, and hospitals last month, it highlighted the potential risks of faulty software updates on vital systems. In a scenario where similar updates impact autonomous vehicles or warehouse robots, the consequences could be even more severe. To address these concerns, Trace Machina, a nascent startup, is developing a solution designed to prevent such issues.

Emerging from stealth mode, Trace Machina has announced a $4.7 million seed investment and introduced its open-source tool, NativeLink. The company’s innovative approach focuses on advanced simulation software that enables developers to rigorously test updates in a realistic simulated environment before deployment.

CEO and co-founder Marcus Eagan explains that Trace Machina’s technology is built on a native, Rust-based system aimed at testing and validating software for autonomous systems, including self-driving cars and warehouse automation equipment. The NativeLink product provides a crucial link between developers and their autonomous systems by offering a staging environment that replicates real-world conditions closely.

Eagan notes that existing development toolkits, like Docker and Kubernetes, fall short when it comes to working with embedded hardware used in autonomous systems. NativeLink addresses this gap by allowing engineers to run experiments and tests directly on local hardware, such as embedded Nvidia GPU chips, which are challenging to source for robots, self-driving cars, and edge devices.

Prior to NativeLink, creating such test environments was typically reserved for well-funded companies or large tech giants like Google. Eagan’s vision is to democratize access to high-fidelity testing environments, making them accessible to a broader range of companies by minimizing the need for a virtualized or abstracted layer that has traditionally been part of these systems.

Eagan’s background includes significant roles at MongoDB, where he contributed to the development of Atlas Vector Search, MongoDB’s first AI product. Co-founder Nathan Bruer brings experience from Google X and the Toyota Institute, where he worked on autonomous vehicle projects.

Eagan’s personal journey is marked by resilience; despite facing racism and overcoming a severe car accident in his youth that left him critically injured, he has persevered to build his company. His determination to succeed and focus on his goals remains unwavering, demonstrating his commitment to advancing the field of autonomous systems and software validation.

The recent seed funding round for Trace Machina has garnered significant backing from several prestigious investors. The round was led by Wellington Management, a major investment firm known for its comprehensive global reach and expertise in identifying promising technologies. Other contributors include Samsung Next, which focuses on advancing innovation and technology; Sequoia Capital Scout Fund, which supports early-stage ventures with high growth potential; Green Bay Ventures, recognized for investing in cutting-edge startups; and Verissimo Ventures, known for its strategic investments in emerging tech. Additionally, several prominent industry angels, individuals with deep expertise and connections in the technology sector, have also joined the round.

This $4.7 million investment is a crucial step for Trace Machina as it continues to develop and refine its advanced simulation software. The funding will be used to enhance their technology, expand their development team, and accelerate the delivery of their solutions to the market. By leveraging this financial support, Trace Machina aims to strengthen its position in the simulation software industry, providing developers with the tools needed to test and validate autonomous systems more effectively and realistically.