Description
DeepFounder AI is an independent software laboratory focused on developing and deploying AI agents, along with the IT infrastructure that makes them dependable in production. Its work spans three areas: designing and building AI agents for real workflows such as customer operations, internal automation, knowledge retrieval, and reporting; building the systems agents depend on, including persistent memory, issue tracking, coordination, and storage; and putting agents into production on your own hardware, self-hosted by default with no data leaving the building unless you choose.
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DeepFounder ships several open products. Castor is a self-hosted AI agent built to drop into business workflows and deploy on a laptop, workstation, or your own server. Mnemos is cloud memory for AI agents, a persistent wiki with sources and an index exposed over REST, MCP, and a CLI. LineAgent is an issue tracker built for AI agents over a single SQLite file, letting agents file, triage, and close their own work. And llm-wiki is an LLM-maintained personal wiki for Claude Code that ingests, synthesizes, cross-links, and reminds.
The lab's principles are that research becomes running software, systems are self-hosted by default, and code, interfaces, and methods are open. It favors plain interfaces (REST, MCP, CLI) built in Rust and Python, and dependable storage, emphasizing precision over surface area. Its projects are published on GitHub.
- CategoryAI Agent Builders
- Pricing ModelOpen source
- DeploymentSelf-hosted
- PlatformsWindows, macOS, Linux
DeepFounder AI's Core Features
Custom AI agents for real business workflows
Castor: self-hosted AI agent that deploys on your own hardware
Mnemos: cloud/persistent memory for agents over REST, MCP, and CLI
LineAgent: issue tracker for agents over a single SQLite file
llm-wiki: LLM-maintained personal wiki for Claude Code
Self-hosted by default, keeping data on your infrastructure
Open code, interfaces, and methods
Plain REST, MCP, and CLI interfaces built in Rust and Python
How to use DeepFounder AI?
Explore the projects: Review DeepFounder's open products on GitHub.
Pick a component: Choose an agent (Castor) or infrastructure like Mnemos or LineAgent.
Self-host it: Deploy on a laptop, workstation, or your own server.
Connect interfaces: Integrate via REST, MCP, or CLI.
Run in production: Put agents and their infrastructure to work on your own hardware.
DeepFounder AI's Use Cases
- Self-hosted AI agents
- Agent memory
- Agent task tracking
- Knowledge management for Claude Code
