Despite their significant potential, AI agents have yet to gain substantial traction in the business world. A new startup emerging from Y Combinator's 2025 summer cohort, Trace, proposes that this slow adoption stems from a lack of contextual understanding. Positioned as a workflow orchestration platform, Trace focuses on mapping intricate corporate environments and processes. This mapping provides AI agents with the necessary context to scale effectively within organizations.

Trace CEO Tim Cherkasov illustrates the company's role by comparing leading AI tools to talented interns. "OpenAI and Anthropic are building these brilliant interns that can be leveraged within the company," he says. "We’re building the manager that knows where to put them."

The London-based company recently announced a $3 million seed funding round. Investors include Y Combinator, Zeno Ventures, Transpose Platform Management, Goodwater Capital, Formosa Capital, and WeFunder. Angel investors Benjamin Bryant and Kevin Moore also participated.

The platform operates by first constructing a knowledge graph from a company's existing digital tools—such as email, Slack, and Airtable—which define daily operations. With this foundational context, users can assign high-level objectives, like "We need to design a new microsite" or "Let's develop our 2027 sales plan." Trace then generates a detailed, step-by-step workflow, intelligently distributing tasks between AI agents and human team members. When an AI agent is engaged, the system supplies it with the precise data required for its specific sub-task.

This approach aims to automate the complex integration of AI agents, which is often a major barrier to their practical deployment in corporate settings. However, Trace enters a competitive landscape, as many firms are now concentrating on agentic AI. Just this week, Anthropic introduced its own enterprise-focused agents, designed with pre-built plugins for departmental functions. Furthermore, many of the productivity platforms Trace interacts with, including Atlassian’s Jira, are developing their own integrated agents, creating potential competition.

Despite this, Trace's founders are confident that their knowledge-graph methodology will distinguish them. They argue that deep "context engineering" is essential for successful agent deployment. CTO Arthur Romanov notes a shift in the industry's focus: "2024 and 2025 was still about prompt engineering. Now we’ve moved from prompt engineering to context engineering." He concludes, "Whoever provides the best context at the right time is going to be the infrastructure on top of which the AI-first companies will be built. And we hope to be that infrastructure."