Freu vs Quartz: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Freu and Quartz — 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
Quartz
datarockets
AI-native email client for Mac that sorts your inbox and drafts replies in your voice, running entirely on-device.
Key features
- On-Device AI: Inbox sorting and reply drafting run locally on Apple Silicon, so email is never sent to external AI providers.
- Importance-Based Triage: Auto-categorizes every message by importance you define and the system learns over time, surfacing what matters and collapsing FYI, Icebox, and Noise.
- Voice-Matched Drafts: Learns your writing style, sender relationship, and thread context to draft replies that sound like you rather than a template.
- Local Encryption: Mail is encrypted on your device with keys only you hold, and the company has no servers that can read it.
- Gmail Integration: Connects to Gmail accounts and has been independently audited under Google's Cloud Application Security Assessment.
Best for
- Inbox Overload: Professionals who get high message volume let Quartz triage by importance so they focus only on mail that needs attention.
- Privacy-Sensitive Email: Users who handle confidential correspondence keep AI processing fully on-device instead of uploading mail to cloud AI services.
- Faster Replies: Drafting routine responses in the user's own voice to cut time spent writing repetitive email.