Sycamore
by Sycamore
The trusted operating system for autonomous enterprise AI agents
Sycamore is an enterprise agent operating system that lets organizations deploy, operate, and scale autonomous AI agents with security, governance, and full operational control. It is built for large enterprises and Fortune 500 teams putting agents into production across workflows like procurement and financial operations.
Sycamore, headquartered in Palo Alto and founded in late 2025 by Sri Viswanath — a former partner at Coatue and former CTO of Atlassian with prior roles at Sun Microsystems, VMware, and Groupon — is building what it calls the trusted operating system for autonomous enterprise AI. The platform spans a five-stage agent lifecycle (discover, build, deploy, observe, and evolve) and centers on 'progressive trust': agents earn greater autonomy as they prove reliability, with full auditability throughout. It supports natural-language-driven generation of production-ready applications, continuous learning from outcomes, and multi-agent coordination that surfaces organizational knowledge. Sycamore emerged with $65 million in seed funding announced March 30, 2026, led by Coatue and Lightspeed Venture Partners with participation from Abstract Ventures, Dell Technologies Capital, 8VC, Fellows Fund, and E14 Fund, plus angels including former OpenAI chief scientist Bob McGrew, Databricks CEO Ali Ghodsi, and Intel CEO Lip-Bu Tan. The company reports early traction with Fortune 500 companies.
At a Glance
- Category
- AI Agents & Orchestration
- Pricing
- Contact for pricing
- Target Market
- CIOs, CTOs, Heads of AI, Enterprise Architects
- Founded
- 2025
- Headquarters
- Palo Alto, United States
- Customers
- Early traction with Fortune 500 companies (customers undisclosed)
Key Features
- ✓Progressive trust autonomy
Agents advance from observation to action as they prove reliability, with full auditability at every step.
- ✓Full agent lifecycle
Covers discover, build, deploy, observe, and evolve stages in a single operating system.
- ✓Natural-language system generation
Generates production-ready applications and agents from natural-language descriptions.
- ✓Continuous learning
Agents improve over time by learning from real outcomes rather than static configuration.
- ✓Multi-agent coordination
Coordinates multiple agents while surfacing and compounding organizational knowledge.
Capabilities
Use Cases
- •Autonomous procurement and finance ops
Deploy governed agents to automate procurement and financial-operations workflows.
- •Enterprise-wide agent governance
Give IT and security teams auditable control over how agents earn and exercise autonomy.
- •Scaling agents to production
Move agent pilots into reliable, monitored production across a Fortune 500 organization.
Ideal For
Best For
- ✓Deploying autonomous AI agents in large enterprises with governance and control
- ✓Managing the full agent lifecycle from build to continuous optimization
- ✓Coordinating multi-agent systems across enterprise workflows
Market & Ratings
Early traction with Fortune 500 companies (customers undisclosed)
Market Analysis
Pros
- ✓Experienced enterprise-infrastructure founding team
- ✓Governance-first 'progressive trust' design
- ✓Large seed round from top-tier investors
Cons
- ✗Very early-stage (founded 2025) with limited public track record
- ✗No public pricing or self-serve access
- ✗Named customers not yet disclosed
Pricing
Enterprise
Contact for pricing
- ✓Agent operating system
- ✓Progressive-trust governance
- ✓Multi-agent coordination
Enterprise-only; pricing is not publicly listed. The company is early-stage and working directly with Fortune 500 customers.
Sources
This page was written from 2 sources, 1 on domains other than sycamore.so.
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