LanMate Overview | LanMate User Guide
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LanMate Overview

LanMate is a local-first AI work execution platform by Lanxin — known in Chinese as 蓝莓办公 (Lanmei Bangong, “Berry Office”). It goes beyond chat — it gets the job done on your local machine: reading and writing files, running code, generating documents, and controlling browsers, with every change producing a reviewable, undoable diff. Once your organization enables it, tasks can also run in a private cloud sandbox.

Core Capabilities

Capability Description
Local Execution Files, code, and data processed entirely on your machine; built-in offline Python environment
MateBot Personal Assistant A sidebar assistant that logs items, watches deadlines, collects messages, dispatches work, and brings receipts back — nothing falls through the cracks (see MateBot)
Cloud Execution Once enabled by your organization, tasks can run in a private cloud sandbox — a second run location alongside local (see Cloud)
Office Documents Built-in Word / Excel / PPT / PDF editors, with 18 official document templates and 16 PPT templates out of the box
Lansenger Collaboration Sign in with Lansenger QR code and bind a personal bot; send commands from your phone, your computer executes, and approval cards reach Lansenger directly
Multi-Agent Orchestration Taskboard dispatch, expert rooms, scheduled jobs — multiple agents working in parallel
Organization Control Three-tier policies for models and skills, server-side API key hosting, full audit trail

Two Surfaces

The board is the project’s execution surface (scheduling, review, branches, worktrees); MateBot is the personal surface (someone owns it, a receipt comes back, someone accepts it). The layers do not replace each other.

Platform Support

Platform Status
macOS Apple Silicon (arm64) Fully supported
Windows x64 Fully supported
Linux (Kylin / UnionTech) Supported (ARM and x86)
HarmonyOS PC Supported (chart generation, diagrams, image cutout, and image/PDF text recognition excluded)

Login Options

Workflow at a Glance

One complete loop of use:

  1. New task: pick a project and run location, describe the need in one sentence — or hand it to MateBot first
  2. Provide context: @ reference files, sessions, or tasks; drag attachments into the composer
  3. Agent executes: tool calls are visible in real time; approval cards pop when confirmation is needed
  4. Review output: diffs, document previews, and files in the right panel
  5. Iterate or deliver: keep refining, or export, commit, and archive

Data is processed locally by default; with cloud execution or organization models enabled, data flows per your organization’s policies. Approval and the sandbox control the boundaries, and artifacts are reviewable and reversible.

Next Steps