Capabilities

OpenHuman Features

Memory, integrations, local storage, model routing, and native tool access — the five areas that determine whether OpenHuman fits your workflow.

OpenHuman Features

Practical notes for evaluating a fast-moving open-source AI assistant.

Practical, source-linked OpenHuman guidance

Feature Areas

Memory Tree

OpenHuman's Memory Tree is a deterministic, bucket-sealed pipeline — not a thin vector-database wrapper. Data from connected accounts converts to Markdown, splits into scored chunks of up to 3,000 tokens, and folds into a hierarchical summary tree stored in local SQLite and an Obsidian-compatible vault.

  • Three conceptual layers: themes (work, family, finance), entities (people, companies, repos), and raw documents (emails, notes, transactions).
  • Relationships between layers are kept explicit so the agent can answer cross-source questions without reloading full context.
  • The vault is inspectable and editable: open it in Obsidian, read or delete chunks, and the agent picks up changes on the next ingest cycle.

Integrations & TokenJuice

118+ third-party integrations via one-click OAuth: Gmail, Calendar, Drive, Notion, GitHub, Slack, Stripe, Linear, Jira, Telegram, Discord, Zoom, Outlook, Dropbox, and more. After the initial exchange, tokens store encrypted in the local vault. TokenJuice then compacts tool output before it reaches any LLM.

  • TokenJuice pipeline: HTML to Markdown, URL shortening, non-ASCII removal, deduplication, and key-info extraction.
  • Maintainer claim: up to 80% reduction in cost and latency. A single-reviewer benchmark reported roughly 70% reduction in one scenario.
  • Background sync runs roughly every 20 minutes for each active connection, folding new content into the Memory Tree.

Model Routing & Local AI

One subscription unlocks 30+ AI providers. The router sends reasoning, agentic, and coding tasks to cloud frontier models; reaction, classification, formatting, sentiment, summarization, and lightweight tasks route locally when local AI is enabled.

  • Local AI is opt-in and off by default. When enabled, supported workloads route to Ollama or LM Studio.
  • Vision tasks are routed to a vision-capable model regardless of local/cloud setting.
  • Optional agentmemory backend lets OpenHuman share the same durable memory store with Claude Code, Cursor, Codex, and OpenCode.

Evaluation Notes

  • Only connect the integrations you actually need — every connector adds attack surface.
  • Know where each task runs: local model, bundled subscription, or external provider.
  • Treat memory as sensitive: it summarizes personal and work data.
  • Voice and Meet use ElevenLabs (cloud TTS) and the Meet API — local-first does not mean local-only.