Sycamore is building what it calls a trusted agent operating system for the enterprise, an infrastructure layer designed to let organizations actually deploy AI agents with trust, governance, and learning built in from day one. Its premise is that the hard part of enterprise agents is not generating them but operating them safely and reliably at scale, which requires security, oversight, and observability woven into the platform rather than added later.
The platform spans the full agent lifecycle: discover, build, deploy, observe, and evolve. Users describe their intent in natural language, and Sycamore generates production-ready systems, including applications, integrations, and agents, tailored to the enterprise environment. Crucially, agents learn from outcomes, improving over time while capturing institutional knowledge across deployments, and every operation is isolated, auditable, and governed from the start.
Sycamore was founded by Sri Viswanath, a former Coatue partner who previously served as a senior executive (CTO) at Atlassian. He left his full-time venture role to start the company and serves as founder and CEO, bringing both investor perspective and large-scale enterprise engineering experience to the agent-infrastructure problem.
The company raised a $65 million seed round led by Coatue and Lightspeed, an unusually large seed that reflects strong conviction. The round included a long list of high-profile angels, among them former OpenAI chief scientist Bob McGrew, Intel CEO Lip-Bu Tan, and Databricks CEO Ali Ghodsi, signaling deep technical and enterprise backing.
Sycamore sits in the enterprise agent control-plane and operating-system category, competing with other companies building governance and orchestration layers for agents. Its differentiation lies in a full-lifecycle approach that combines natural-language system generation, built-in governance and isolation, and agents that learn and retain institutional knowledge, all under a single trusted operating system for enterprise autonomy.