Open source

The platform is public. The engineering is the value.

We open source what we build. Three projects under github.com/Simple4uhq — the multi-tenant AI agent platform we run for clients, the persistent memory MCP server we use ourselves, and the self-hosted trust standard we score against. Apache 2. Free to self-host. Engagement is for the engineering capability that runs them.

Public repositories

Three projects, one philosophy.

Each one solves a real problem we encountered building production AI infrastructure. Each one is something we still use ourselves. Each one is yours to fork.

SAE4U Agent · Apache 2

Multi-tenant AI agent platform

The orchestrator + per-tenant runtime template we built and use for paid AI Infrastructure engagements.

FastAPI control plane on dedicated ops-master, per-tenant DigitalOcean droplets via DO API + cloud-init, Fernet-encrypted bot pool, Telegram-first agent runtime with FTS5 + sqlite-vec hybrid knowledge base. Includes ARCHITECTURE.md narrative documenting what we built, what we learned, and why we walked away from selling it as SaaS.

Python · FastAPI · SQLite · Apache 2 · self-hostable
View on GitHub → Hire us to run it →
simple4u-memory · MIT

Persistent memory MCP server for Claude Code

Two-corpus recall (SQLite + markdown), customizable persona, hierarchical memory architecture.

MCP (Model Context Protocol) server for Claude Code adding persistent memory across sessions. Two-corpus recall: structured facts in SQLite via tagged categories, plus markdown files for narrative memory. Default persona rules-based, customizable per workspace. Available on PyPI, install with `pip install simple4u-memory`.

Python · MCP · SQLite + FTS5 · PyPI · Claude Code
View on GitHub → Install from PyPI →
SHAITS · Open spec

Self-Hosted AI Trust Standard

Open specification for trustworthy self-hosted AI agents. We score against it ourselves.

A 125-point scoring framework for self-hosted AI: data residency, audit logging, telemetry policy, encryption at rest, key rotation, dependency provenance. Cloud-only products are out of scope by design. We publish our own self-audit using the standard. Other self-hosted projects encouraged to audit + register.

Open spec · markdown · self-audit framework
View on GitHub → Read the standard →
Why open source

No proprietary moat. The engineering is the moat.

Most AI consulting firms keep their tooling proprietary. We took the opposite stance. The reason: clients shouldn't be locked into our tools — they should pick us because the engineering is real, not because we hold their AI hostage. When you engage us, you get a deployment of the same code we publish on GitHub. You can fork, audit, run elsewhere if our engagement ever ends. Trust comes from full visibility, not from contractual lock-in.

Practically: this also doubles as our most credible lead-gen channel. Developers find the code, read the engineering, decide we're real, contact us. That's better signal than any landing page can produce alone.

Want to engage us, or contribute, or just self-host?

All three are welcome. Engagement = paid retainer for the engineering team that runs this code. Contribute = PRs welcome on all three repos. Self-host = fork, run, never talk to us.

Book 15 min →