Dedalus Labs builds a compute substrate for AI agents, described as the fastest persistent computer for agents, enabling developers to host long-running, stateful AI agents with response times under 250ms. Its open-source SDK connects any LLM to MCP (Model Context Protocol) servers without Docker or complex configuration, letting developers build complex agents in roughly five lines of code with vendor-agnostic model handoffs and real-time streaming. Founded in 2025, Dedalus is based in San Francisco and was part of Y Combinator's Summer 2025 batch. The company raised an $11M seed round co-led by Kindred Ventures and Saga Ventures.
Dedalus Labs
ActiveCompute substrate for AI agents
Total raised
$11.5M
2 rounds
Stage
Seed
Oct 2025
Team
1-10
since 2025
Pricing
—
Founded
2025
San Francisco, United States
Agent-ready
—
Compute substrate for hosting long-running, stateful AI agents
Sub-250ms agent response latency
Open-source SDK connecting any LLM to MCP servers
No Docker or complex configuration required to get started
Build complex agents in roughly five lines of code
Vendor-agnostic model handoffs across LLM providers
Real-time streaming of agent responses
Persistent agent state for durable, long-lived workflows
12/100
Early
MCP server
Public API
Webhooks
OAuth 2.0
SDKs
No public agent surfaces detected yet.
Cumulative raise
From 2025 to 2026 · 2 rounds tracked
Total
$11.5M
Oct 2025 Seed $11M ● Kindred Ventures
Jan 2025 Seed $500K ● Y Combinator
Capital network
$11.5M raised ·13 backers·10 network links
- Backers13
- Shared portfoliocompanies these backers also fund
- Extended networkfunds that co-invest alongside them
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- What is Dedalus Labs?
- Dedalus Labs builds a compute substrate for AI agents, hosting long-running stateful agents with sub-250ms latency and providing an open-source SDK that connects any LLM to MCP servers.
- How quickly can I build an agent?
- Its SDK is designed to let developers build complex agents in roughly five lines of code, without Docker or complex configuration.
- Is it tied to a specific LLM provider?
- No. The platform is vendor-agnostic and supports model handoffs across different LLM providers.
- What is MCP and why does it matter here?
- MCP (Model Context Protocol) is a standard for connecting models to tools and data; Dedalus connects any LLM to MCP servers so agents can use external capabilities.
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