Henji vs Keel — An AI assistant whose memory belongs to you.: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Henji and Keel — An AI assistant whose memory belongs to you. — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Henji
Henji
Mac app that drafts chat and email replies in your own voice across Slack, LINE, Gmail, and Messages.
Key features
- Voice Matching: Learns your usual tone and phrasing over time so replies read as you-ish rather than AI-ish.
- Tone Modes: Switch between Polite, Casual, Team, and Friends styles so each reply fits the relationship and channel.
- Multi-Channel Coverage: Works across Slack, LINE, Gmail, and Messages so chat and email replies are handled in one place.
- Scribble-to-Reply: Type a short note or intent and Henji expands it into a complete, context-aware message.
- Multilingual: Supports multiple languages including English and Japanese for replies.
Best for
- Faster Messaging: Knocking out quick chat and email replies during a busy day without sounding robotic.
- Difficult Replies: Politely declining requests or negotiating deadlines while keeping the tone warm.
- Team Communication: Keeping internal Slack threads fast and to the point with a team-appropriate tone.
- Cross-Language Correspondence: Drafting replies in English or Japanese for international contacts.
Keel — An AI assistant whose memory belongs to you.
Keel Labs
Local-first desktop assistant for Mac/Windows that stores plain Markdown on your disk and lets you swap models while keeping your context.
Key features
- Local-First Storage: Stores all assistant memory and workspace data as plain Markdown files on the user's disk to ensure portability, offline access, and easy backup/versioning with Git.
- Model-Agnostic Integration: Supports swapping between model providers (e.g., Claude, GPT, OpenRouter, Ollama) allowing users to change inference backends without losing context or notes.
- Plain Markdown Workspace: Uses human-readable Markdown as the native data format, enabling easy editing, searching, and integration with existing text-based workflows and tools.
- Cross-Platform Desktop App: Provides a native desktop experience for both macOS and Windows users optimized for local performance and file-system based storage.
- Privacy-First Design: Keeps context and memory under user control by defaulting to local storage and enabling use of local or self-hosted model endpoints.
- Bring-Your-Own-Model (BYOM): Allows connecting to local or third-party model runtimes (e.g., Ollama or OpenRouter) so users can run models they trust or prefer.
- Open Source Repository: Project source and releases are available on GitHub, facilitating community contributions, audits, and self-hosted deployments.