AI agents have significant potential but have struggled to impact enterprises due to a lack of context, according to a new startup. Trace, launched through Y Combinator’s 2025 summer cohort, aims to solve this with workflow orchestration. They map corporate environments to provide context for AI agents to scale effectively.
Trace CEO Tim Cherkasov highlights how OpenAI and Anthropic provide AI tools, while Trace acts as the manager placing them effectively. The London-based company announced a $3 million seed funding raise from investors including Y Combinator, Zeno Ventures, and more, with angel investors Benjamin Bryant and Kevin Moore participating.
Trace’s system creates a knowledge graph from corporate tools like email and Slack, allowing users to input tasks such as “design a new microsite” or “develop a 2027 sales plan.” The system then devises a workflow, allocating tasks to AI and human workers. When engaging AI, it supplies the necessary data for the task.
The goal is to simplify onboarding AI agents, addressing a significant deployment barrier. Despite competition from companies like Anthropic and Atlassian releasing their AI solutions, Trace believes its knowledge-graph strategy will prevail.
Trace’s approach emphasizes context engineering over prompt engineering—a shift in AI development focus. CTO Artur Romanov asserts that providing timely, effective context will define AI infrastructure, with Trace aspiring to lead in this domain.