Trace: Aiming to Enhance the Deployment of AI Agents in Business Environments
Artificial Intelligence (AI) agents have the potential to revolutionize businesses, but their impact has been slower than expected. The primary roadblock is the lack of context within which these AI agents operate. However, a new startup called Trace, part of Y Combinator’s Summer 2025 cohort, is aiming to address this challenge.
Mapping Complex Business Environments
Trace is a workflow orchestration startup that maps complex business environments and processes. This gives AI agents the necessary context to evolve rapidly. CEO of Trace, Tim Cherkasov, compares the role of his company to a manager who knows where to place the interns trained by AI labs like OpenAI and Anthropic. “We train the manager who knows where to place them,” he says.
Funding and Future Plans
On Thursday, Trace announced that it had raised $3 million in seed funding. The investors include Y Combinator, Zeno Ventures, Transpose Platform Management, Goodwater Capital, Formosa Capital, and WeFunder. Notable angel investors Benjamin Bryant and Kevin Moore also participated in the funding round.
How Does Trace Work?
Trace’s system works by creating a knowledge graph of a company’s existing tools such as email, Slack, and Airtable, which are integral to the company’s daily operations. With this context in place, users can ask the system for high-level tasks like designing a new microsite or developing a sales plan. Trace then comes back with a step-by-step workflow, delegating some tasks to AI agents and assigning others to human workers. It effectively automates the integration of AI agents, a significant hurdle to effective deployment within companies.
Competition and The Way Forward
Despite the intense competition in the field of agentic AI, Trace’s founders are confident in their unique approach. They believe their knowledge graph-based system, which integrates contextual engineering deep into the agent deployment framework, will be a game-changer. This approach is a shift from the rapid engineering trend of 2024 and 2025 towards contextual engineering.
CTO Artur Romanov says, “Whoever provides the best context at the right time will be the infrastructure on which AI-driven businesses will be built. And we hope to be that infrastructure.”
With its fresh funding and innovative approach, Trace is all set to make a significant impact on the deployment of AI agents in businesses. The future of AI-driven businesses appears to be promising, thanks to companies like Trace.
To learn more about Trace and their innovative work, click Here.
