Freu vs Henji: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Freu and Henji — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Freu
Freu AI (freu-ai)
Ahead-of-time web automation that records browser sessions and compiles them into reusable deterministic skill commands to reduce agent token use.
Key features
- Ahead-of-Time Compilation: Records a browser session once (via Chrome extension and CDP) and compiles it into a reusable JSON-based DSL skill that agents can execute deterministically.
- Token Usage Reduction: Offloads repeated visual and reasoning steps to compiled programs, reducing LLM/agent token consumption (repo claims up to ~90% savings) and lowering recurring inference costs.
- Chrome Extension + CDP Runner: Captures user interaction and driving Chrome DevTools Protocol commands for precise, reproducible playback and capture of complex UI flows.
- Skill DSL & Artifacts: Emits human- and agent-readable artifacts (SKILL.md and <Cmd>.json steps) that document the workflow, provide structured muscle memory, and enable auditing and reuse.
- Local HTTP Bridge: Runs a Python HTTP service (default 127.0.0.1:8787) to serve skills to agents and orchestrate learn/run cycles programmatically.
- Deterministic Execution: Converts volatile DOM parsing and visual reasoning into stable, deterministic commands so agents can skip expensive visual interpretation.
- Extensibility Toward Desktop: Roadmap includes an OS-level Computer Use Agent (CUA) and vision-based desktop automation to extend AOT pipeline beyond browsers.
- Record browser sessions via a Chrome extension and CDP command runner
- Compile recorded sessions into reusable, deterministic JSON skill files (DSL)
- Local Python HTTP bridge (freu-cli) that communicates with the Chrome extension (default 127.0.0.1:8787)
- Outputs SKILL.md and <Cmd>.json structured steps suitable for agent consumption
- Reduces LLM token usage by delegating repeated deterministic actions to compiled skills
- Logging and intermediate artifact generation during learn/run workflows
- CLI-based workflow: learn (capture + LLM) and run (execute compiled skill)
- Planned extension to OS-level vision-based desktop automation (Computer Use Agent)
Best for
- Automating repetitive web workflows (form submission, navigation, multi-step interactions) by recording once and replaying as a compiled skill.
- Reducing LLM/agent operating costs by converting expensive, repeated web reasoning into deterministic skills loaded into the agent context.
- Building stable enterprise automation where auditability and reproducibility are required—SKILL.md and JSON steps provide documented, inspectable workflows.
- Integrating precompiled skills into agent pipelines via the local HTTP bridge to coordinate when and how skills are executed programmatically.
- Creating reusable automation libraries across teams: capture a complex sales/CRM flow once and share the compiled skill for consistent execution.
- Translating human-performed browser sessions into structured automation artifacts for testing, monitoring, and regression checks.
- Stabilize and accelerate complex enterprise web workflows by precompiling repetitive tasks
- Reduce costs for LLM-enabled agents by offloading deterministic UI interactions to compiled skills
- Build reusable skill libraries for agent-driven automation and RPA-like tasks
- Automated end-to-end test recording and deterministic playback for web applications
- Integrate precompiled web skills into agent context windows to avoid DOM re-parsing
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.