Honcho
What is Honcho?
Honcho is an AI-native memory platform for building stateful AI agents. It stores and indexes messages, continuously reasons about interactions through its Neuromancer models, and returns curated context through a simple context() method. Honcho helps agents maintain continuity, understand user preferences, reduce unnecessary token usage, and support advanced reasoning across users, agents, NPCs, groups, and other entities. It supports model-agnostic integrations, unlimited retrieval, token budgets, peer scoping, background dreaming, and on-demand reasoning.
How to use Honcho?
Create a Honcho workspace, connect an AI agent or supported integration, and write conversation messages to Honcho. The platform automatically stores, indexes, and reasons over the messages. Call context() to retrieve curated memory and conversation history with controls such as token limits, search, summaries, and peer targeting. For specific questions, use .chat() with a selected reasoning tier. Honcho can also be integrated through its CLI, Claude Code, OpenAI Codex, OpenClaw, Hermes Agent, and DeepSeek Harness plugins.
Honcho's Core Features
Automatic message ingestion, indexing, and continual reasoning
Curated context retrieval through context()
Token-budgeted context generation for lower usage and cost
On-demand reasoning through multiple .chat() tiers
Unlimited memory retrieval
Background dreaming for asynchronous pattern identification and inference
Peer-based memory for users, agents, NPCs, groups, and relationships
Scoped perspectives and granular session management
Model-agnostic support for OpenAI, Anthropic, and custom models
Integrations for Claude Code, OpenAI Codex, OpenClaw, Hermes Agent, and DeepSeek Harness
Production support for stateful AI applications
Honcho's Use Cases
Build coding agents that remember team conventions, architecture preferences, and prior code reviews
Create AI companions with persistent relationships, emotional continuity, and preference alignment
Develop NPCs that form opinions, remember relationships, and adapt game narratives
Provide customer support agents with persistent context across sessions, channels, and handoffs
Build educational tutors that track misconceptions and adapt difficulty over time
Create productivity agents that preserve workflow context across tools and sessions
Support multi-agent or group conversations with scoped peer perspectives
FAQ from Honcho
What is Honcho used for?
How does Honcho store and retrieve memory?
What is the context() method?
Does Honcho support multiple types of entities?
What is Honcho dreaming?
How much does Honcho cost?
Does Honcho offer a free plan?
Honcho Reviews (0)
Honcho Pricing
Honcho Memory
$2.00 per million context tokens
Message ingestion, storage, and Neuromancer reasoning. context() has no stated retrieval limit and typically responds in approximately 200 milliseconds.
Dreaming
Included
Background inference for continual learning is included with every workspace.
Minimal Reasoning
$0.001 per query
Instant single semantic search for simple lookups.
Low Reasoning
$0.01 per query
Instant conclusions with surrounding context; described as the default tier.
Medium Reasoning
$0.05 per query
Fast multiple-search reasoning with directed synthesis.
High Reasoning
$0.10 per query
Asynchronous multi-pass analysis for deeper synthesis.
Max Reasoning
$0.50 per query
Asynchronous research-grade analysis using exhaustive history search and quantitative methods.
Startup Program
$1,000 in credits
Available to startups that have raised less than $5 million, with 12 months of subsidized pricing and integration support. Application required.
Enterprise
Custom pricing
Custom plans with forward-deployed engineers and dedicated integration and maintenance support.
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