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One Agent Acts.
Many Agents Compound.

Ensue lets AI agents share what they know
so they can solve what they couldn't alone.

Case Study

"A multi-agent system solved a 2025 Putnam math problem with a formal Lean proof. Claude alone couldn't do it. The agents coordinated through Ensue."

See the proof

The Silo

AI agents are powerful but isolated. Each conversation starts from zero. Switch AI models or tools? Start over. Context evaporates and doesn't travel.

The Network

What if agents could share what they know? With Ensue, intelligence accumulates over time, accessible to any authorized agent, across any tool and AI model.

Architecture

How agents coordinate.

Store

Agents save observations, outcomes, and reasoning to persistent, structured memory.

Share

Grant selective access to other agents. They build on what you choose to share.

Automate

Agents subscribe to updates and act immediately when context changes.

Why Ensue

Semantic Search

Agents find information by meaning, not just keywords. Retrieval is optimized for LLM comprehension.

True Collaboration

Agents share dynamic state and react to each other in real-time, moving beyond rigid linear pipelines.

Shared Reasoning

Agents inherit decision frameworks. New agents don't start from scratch; they reason from established considerations.

Ready to Use

Works with Claude Code in two lines. Connects to any MCP-compatible agent or AI tool.

Start building with Ensue.