Trace raises $3M to solve the AI agent adoption problem in enterprise

Source: TechCrunch

For all their potential, AI agents have been slow to make an impact in the enterprise, and one new startup is betting that the reason they haven’t is a lack of context.

Launched as part of Y Combinator’s 2025 summer cohort, Trace is a workflow‑orchestration startup aimed at filling that gap. The company maps complex corporate environments and processes so that agents have the context they need to scale quickly.

“OpenAI and Anthropic are building these brilliant interns that can be leveraged within the company,” says Trace CEO Tim Cherkasov, referring to the AI labs’ tools. “We’re building the manager that knows where to put them.”

Funding

On Thursday, the London‑based company announced a $3 million seed round led by Y Combinator, Zeno Ventures, Transpose Platform Management, Goodwater Capital, Formosa Capital, and WeFunder. Angel investors Benjamin Bryant and Kevin Moore also participated.

How Trace Works

Trace’s system starts by building a knowledge graph from a company’s existing tools—systems like email, Slack, and Airtable that shape day‑to‑day work. With that context in place, users can prompt the system with a high‑level task (e.g., “We need to design a new microsite” or “Let’s develop our 2027 sales plan”). Trace then returns a step‑by‑step workflow, delegating some tasks to AI agents and assigning others to human workers. When an AI agent is invoked, it receives the specific data needed to complete its sub‑task.

The goal is to automate the delicate work of onboarding AI agents, one of the biggest blockers to actual deployment within companies.

Competition

The enterprise‑agent space is becoming crowded:

• Anthropic recently launched its own enterprise‑agent offering, focused on pre‑built plugins for finance, engineering, and design — see the announcement here.
• Major workplace‑productivity platforms that Trace integrates with, such as Atlassian’s Jira, are also introducing their own agents, potentially competing directly with Trace’s system — read more here.

Vision

“2024 and 2025 was still about prompt engineering. Now we’ve moved from prompt engineering to context engineering,” says CTO Arthur Romanov. “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.”