We build AI agents — and the infrastructure they run on.
DeepFounder AI is an independent software laboratory focused on developing and deploying AI agents, and the IT infrastructure that makes them dependable in production — memory, tooling, coordination, and storage.
Agent development
We design and build AI agents for real workflows — customer ops, internal automation, knowledge retrieval, reporting. Grounded in research into how agents behave outside the demo.
Agent infrastructure
The systems agents depend on: persistent memory, issue tracking, coordination, and storage. Plain interfaces — REST, MCP, CLI — built in Rust and Python, released in the open.
Deployment & self-hosting
We put agents and their infrastructure into production on your hardware — a laptop, a workstation, or your own server. Self-hosted by default, no data leaving the building.
castor
A self-hosted AI agent built to drop into business workflows — customer ops, internal automation, knowledge retrieval, scheduled reporting. Deploys on a laptop, a workstation, or your own server.
mnemos
Cloud memory for AI agents — a persistent wiki with sources and an index, exposed over REST, MCP, and a CLI.
LineAgent
An issue tracker built for AI agents — REST, MCP, and CLI over a single SQLite file. Agents file, triage, and close their own work.
llm-wiki
An LLM-maintained personal wiki for Claude Code. An active librarian: it ingests, synthesizes, cross-links, and reminds.
Research becomes software
Every line of inquiry ends in a running system. If a finding can't survive deployment, it isn't finished.
Self-hosted by default
Our systems run on your hardware — no mandatory cloud, no data leaving the building unless you send it.
Open by default
Code, interfaces, and methods are public. We keep the weights of our attention on problems, not on secrecy.
Small and exact
A small team, plain interfaces — REST, MCP, CLI — and boring, dependable storage. Precision over surface area.