Honcho

Honcho is an AI-native memory platform designed for building stateful AI agents that actually remember. Instead of starting every session from scratch, your agents can maintain continuity across conversations and genuinely understand user preferences over time.

Under the hood, Honcho stores and indexes messages, then continuously reasons about interactions through its Neuromancer models. When your agent needs context, it simply calls a straightforward context() method and receives curated, relevant information instead of raw history.

This approach helps reduce unnecessary token usage, which means lower costs and faster responses. Honcho also supports advanced reasoning across users, agents, NPCs, groups, and other entities, making it well suited for multi-agent systems, games, and collaborative applications.

Integration is model-agnostic, so you can plug it into whichever LLM you prefer. The platform includes unlimited retrieval, token budgets, peer scoping, background dreaming, and on-demand reasoning, giving you fine-grained control over how and when context is delivered.