Glen

Glen is an organization-wide memory layer designed for AI agents, giving them a shared, persistent knowledge base that evolves over time. Instead of each agent operating in isolation, Glen ensures that what one agent learns becomes available to all others, improving consistency and reducing duplication of work. Its primary purpose is to centralize institutional knowledge so every agent can act with the context and judgment of your best performers from day one.

Glen continuously collects and structures interactions, decisions, and outcomes into reusable “memories,” then automatically clusters these into higher-level skills. These skills can be invoked by any connected agent through standard interfaces such as MCP and plugins, allowing easy integration into existing AI workflows and orchestration layers. Glen’s memory system supports read and write operations, so agents can both consume past knowledge and contribute new learnings as they work. This creates a feedback loop where performance improves over time without manual prompt engineering or hard-coded rules.