rowboatlabs/rowboat

**rowboatlabs/rowboat**

Open-source AI coworker, with memory Rowboat Open-source AI coworker that turns work into a knowledge graph and acts on it Rowboat connects to your email and meeting notes, builds a long-lived knowledge graph, and uses that context to help you get work done - privately, on your machine. You can do things like: Build me a deck about our next quarter roadmap → generates a PDF using context from your knowledge graph Prep me for my meeting with Alex → pulls past decisions, open questions, and relevant threads into a crisp brief (or a voice note) Visualize, edit, and update your knowledge graph anytime (it’s just Markdown) Record voice memos that automatically capture and update key takeaways in the graph Download latest for Mac/Windows/Linux: Download Demo Watch the full video Installation Download latest for Mac/Windows/Linux: Download All release files: https://github.com/rowboatlabs/rowboat/releases/latest Google setup To connect Google services (Gmail, Calendar, and Drive), follow Google setup. Voice notes To enable voice notes (optional), add a Deepgram API key in ~/.rowboat/config/deepgram.json: { "apiKey": "<key>" } What it does Rowboat is a local-first AI coworker that can: Remember the important context you don’t want to re-explain (people, projects, decisions, commitments) Understand what’s relevant right now (before a meeting, while replying to an email, when writing a doc) Help you act by drafting, summarizing, planning, and producing real artifacts (briefs, emails, docs, PDF slides) Under the hood, Rowboat maintains an Obsidian-compatible vault of plain Markdown notes with backlinks — a transparent “working memory” you can inspect and edit. Integrations Rowboat builds memory from the work you already do, including: Gmail (email) Granola (meeting notes) Fireflies (meeting notes) How it’s different Most AI tools reconstruct context on demand by searching transcripts or documents. Rowboat maintains long-lived knowledge instead: context accumulates over time relationships are explicit and inspectable notes are editable by you, not hidden inside a model everything lives on your machine as plain Markdown The result is memory that compounds, rather than retrieval that starts cold every time...

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