honcho

To set up cross-session memory for Hermes agents, ask Hermes to configure Honcho by saying “Set up Honcho for my profile.” This integrates the honcho-ai Python package to enable persistent user modeling across conversations.

Cross-session user memory continuously learns about a user across separate conversations to eliminate fragmented context. It works by maintaining a unified user view while isolating distinct AI peers for each Hermes profile.

Yes, you can use separate Hermes profiles for different asset classes while sharing the same user context. Multi-profile peer isolation gives each profile its own AI personality while retaining a unified user view for personalized insights.

Available recall modes for configuring user memory observations include hybrid, context, and tool modes. These allow you to fine-tune what user information is remembered and how it is accessed during Hermes agent sessions.

Yes, Honcho memory supports both cloud and self-hosted deployments. This flexibility allows you to choose your preferred infrastructure environment when configuring cross-session memory for Hermes agents in finance workflows.

Cross-session memory eliminates the need for manual state management by automatically persisting user context across conversations. This prevents fragmented context loss, enabling continuous personalized insights in finance and research workflows.