Rowboat: The Open-Source AI Coworker That Actually Remembers

Rowboat is an open-source AI coworker that connects to your email, meeting notes, and work data to build a persistent knowledge graph—enabling it to remember context across conversations and help you prepare for meetings, draft emails, and generate documents grounded in your actual work history. Unlike proprietary AI assistants that reconstruct context on demand, Rowboat maintains long-lived knowledge that compounds over time, storing everything locally as plain Markdown files you own and control.

What is Rowboat?

Rowboat is a local-first AI coworker developed by Rowboat Labs and released as open-source software on GitHub. It distinguishes itself from mainstream AI assistants through two core design principles: persistent memory and local data ownership.¹

At its foundation, Rowboat integrates with tools you already use—Gmail, Google Calendar, Granola (meeting notes), and Fireflies—to automatically extract and organize information into an Obsidian-compatible vault of Markdown notes with backlinks.¹ This “working memory” is transparent and fully editable, unlike the hidden vector stores used by most AI applications.

💡 Tip: Rowboat’s Markdown vault format means your data remains accessible even if you stop using the application. The Obsidian-compatible format ensures long-term portability.

The project exists in two forms:

1. Rowboat Desktop – A local-first AI coworker that runs on your machine (Mac, Windows, Linux) with full data privacy
2. Rowboat Studio – A low-code web IDE for building and deploying multi-agent AI assistants via API²

This dual approach makes Rowboat unique: it serves both as a personal productivity tool and as a platform for developers building AI-powered applications.

How Does Rowboat Work?

Knowledge Graph Architecture

Rowboat’s memory system operates as a knowledge graph rather than a simple retrieval system. When you connect your accounts, Rowboat processes emails and meeting transcripts to extract:¹

• People – Contacts you interact with, their roles, and your history together
• Projects – Ongoing initiatives, their status, and associated stakeholders
• Decisions – Choices made in meetings with their rationale and implications
• Commitments – Action items, deadlines, and promises extracted from conversations
• Open questions – Unresolved items requiring follow-up

These entities are linked through explicit relationships in a graph structure stored as interconnected Markdown files. The result is memory that compounds—each new piece of information enriches the existing context rather than replacing it.

Background Agents

Rowboat can deploy background agents that perform routine work automatically:¹

• Drafting email replies grounded in your past context and commitments
• Generating daily voice notes summarizing your agenda and priorities
• Creating recurring project updates from recent emails and notes
• Keeping the knowledge graph updated as new information arrives

You control what runs, when it runs, and what gets written back to your local vault.

MCP Integration

Rowboat extends its capabilities through the Model Context Protocol (MCP), an open standard for connecting AI applications to external tools.³ This enables integration with:¹

• Exa (web search)
• Twitter/X
• ElevenLabs (voice synthesis)
• Slack
• Linear/Jira
• GitHub

ℹ️ Info: MCP is like “USB-C for AI applications”—a standardized way to connect AI systems to external data sources and tools, developed by Anthropic and hosted by the Linux Foundation.³

Multi-Model Support

Rowboat does not lock you into a single AI provider. You can use:¹

• Local models via Ollama or LM Studio
• Hosted models with your own API key
• Swap models anytime—your data remains in your local Markdown vault

Why Does Rowboat Matter?

The Memory Problem in AI Assistants

Most AI tools reconstruct context on demand by searching transcripts or documents. This approach has three fundamental limitations:

1. Cold starts – Each conversation begins with limited context
2. Ephemeral knowledge – Important details are lost between sessions
3. Opaque storage – Users cannot inspect or edit what the AI “knows”

Rowboat addresses each of these issues through its persistent, inspectable knowledge graph architecture.

Data Privacy by Design

In an era of increasing concern over AI data usage, Rowboat’s local-first architecture offers a compelling alternative:¹

Open Source Benefits

As an open-source project (available at github.com/rowboatlabs/rowboat), Rowboat offers advantages proprietary alternatives cannot match:¹

• Code transparency – Audit exactly how your data is processed
• Community contributions – Benefit from collective improvements
• No vendor lock-in – Self-host or modify as needed
• Free to use – No subscription fees for the core product

Rowboat vs. Proprietary Alternatives

The AI coworker space is crowded with well-funded competitors. Here’s how Rowboat compares to the leading alternatives:

Rowboat vs. Claude Code

Claude Code, developed by Anthropic, is one of the most capable AI coding assistants available.⁴ It offers:⁴

• File editing and command execution
• Codebase understanding across multiple files
• Git integration for commits and pull requests
• MCP support for external tool connections

However, Claude Code operates primarily as a session-based tool without persistent memory between conversations. Each interaction starts fresh, requiring you to re-establish context. Rowboat’s knowledge graph persists across sessions, maintaining accumulated understanding of your work, relationships, and projects.

Claude Code also requires a $20/month subscription,⁵ while Rowboat is free and open-source.

Rowboat vs. GitHub Copilot

GitHub Copilot is the most widely adopted AI developer tool, with millions of individual users and tens of thousands of business customers.⁶ GitHub reports that developers using Copilot are up to 55% more productive at writing code and report up to 75% higher job satisfaction.⁶

Copilot has expanded beyond code completion to include:⁷

• Copilot coding agents – Autonomous agents that write code and create pull requests
• Multi-model support – Choose from GPT-4, Claude, and other models
• MCP integration – Connect to external tools and data sources

However, Copilot remains focused on software development workflows. Rowboat extends AI assistance to general knowledge work—meetings, emails, document creation, and project management—while maintaining the same local-first, privacy-preserving architecture.

What Does Rowboat Mean for Team Workflows?

Meeting Preparation Reimagined

Rowboat transforms how professionals prepare for meetings. Instead of searching through email threads and meeting notes, you can simply ask:¹

“Prep me for my meeting with Alex”

Rowboat pulls past decisions, open questions, and relevant threads into a concise brief—or even a voice note you can listen to while commuting.

Context-Aware Communication

When drafting emails, Rowboat grounds suggestions in your actual history and commitments with each recipient. This eliminates the cognitive overhead of remembering what was promised, what remains pending, and what tone is appropriate for each relationship.

Document Generation

Rowboat can generate documents and presentations from your ongoing context:¹

“Build me a deck about our next quarter roadmap”

The resulting PDF incorporates context from your knowledge graph, ensuring alignment with actual decisions and project status rather than generic templates.

The Compound Knowledge Effect

Traditional AI assistants treat each interaction as independent. Rowboat’s knowledge graph creates a compound effect: each meeting, email, and note enriches the context for future interactions. Over time, the assistant becomes increasingly attuned to your work patterns, relationships, and priorities.

Getting Started with Rowboat

Installation

Rowboat is available for Mac, Windows, and Linux through GitHub Releases:¹

# Download from the official repository
https://github.com/rowboatlabs/rowboat/releases/latest

Configuration

To enable full functionality, you’ll need to configure:

1. Google services – Connect Gmail, Calendar, and Drive¹
2. Deepgram API key – For voice note transcription (optional)¹
3. Brave or Exa API key – For web search capabilities (optional)¹
4. Model provider – Local (Ollama/LM Studio) or hosted API

Building Multi-Agent Assistants (Studio)

For developers, Rowboat Studio provides a visual interface for creating complex multi-agent systems:²

Limitations and Considerations

As an open-source project in active development, Rowboat has some constraints:

• Setup complexity – Requires more initial configuration than commercial alternatives
• Model costs – Using hosted models requires your own API key and associated costs
• Feature maturity – Some capabilities may lag behind well-funded proprietary tools
• Community size – Smaller ecosystem than major commercial platforms

⚠️ Warning: Rowboat’s local-first approach means you are responsible for your own data backups. Unlike cloud services, there is no automatic recovery if you lose your local vault.

The Future of AI Coworkers

Rowboat represents a growing movement toward sovereign AI—artificial intelligence systems that users own, control, and operate independently of large technology platforms. This approach addresses three converging trends:

1. Privacy concerns – Growing awareness of data exploitation by AI companies
2. Regulatory pressure – Increasing requirements for data localization and transparency
3. Technical maturation – Open-source models approaching commercial quality

At time of writing, the open-source AI landscape is evolving rapidly. Rowboat’s integration of persistent memory, local data ownership, and multi-agent capabilities positions it as a compelling alternative for privacy-conscious professionals and organizations seeking to maintain control over their AI tools.

Frequently Asked Questions

Q: What makes Rowboat different from other AI assistants like ChatGPT or Claude? A: Rowboat’s key differentiators are persistent memory through a knowledge graph and local data storage. While ChatGPT and Claude reconstruct context per session, Rowboat maintains long-term memory across all your work. Additionally, Rowboat stores data locally as Markdown files you control, rather than in proprietary cloud systems.

Q: Is Rowboat free to use? A: Yes, Rowboat is open-source and free to use. You may incur costs for API keys if using hosted AI models (OpenAI, Anthropic, etc.), but the core application has no subscription fees. Local models via Ollama or LM Studio operate entirely cost-free.

Q: How does Rowboat handle data privacy? A: Rowboat operates on a local-first architecture. Your emails, meeting notes, and knowledge graph are stored locally as Markdown files on your machine. No work data is sent to Rowboat’s servers—you maintain complete ownership and control.

Q: Can Rowboat integrate with my existing tools? A: Yes, Rowboat supports integrations with Gmail, Google Calendar, Granola, Fireflies, Slack, Linear, Jira, GitHub, and more through MCP (Model Context Protocol). The open-source nature also allows community contributions for additional integrations.

Q: What is Rowboat Studio and how is it different from Rowboat Desktop? A: Rowboat Desktop is the personal AI coworker application for individual productivity. Rowboat Studio is a web-based IDE for developers to build and deploy multi-agent AI applications via API. Studio is designed for creating AI-powered services, while Desktop is for personal workflow enhancement.

Rowboat represents a fundamental shift in how we think about AI assistants—not as opaque cloud services that rent access to our own data, but as transparent, locally-operated tools that amplify human capability while respecting privacy and autonomy. For professionals seeking AI assistance without sacrificing data ownership, Rowboat offers a compelling path forward.