Open source · Self-hosted

Open-source AI platforms for your team, running on your own infrastructure

GreenOnGrey builds two products. Nabu gives every employee a personal AI agent. Hammurapi runs the product development cycle with an AI agent as a partner.

GreenOnGrey logo: a blade of grass growing through a cracked grey stone

Principles

Open source

Apache 2.0. The code and the documentation are public, including the limits we know about.

On your infrastructure

Both products run on your servers, with the models you choose. Nothing is hosted by us.

People decide

Agents do the work between decisions. Approvals, signatures and releases stay with people, and every tool call is audited.

early stage

Nabu

An on-premises platform of AI agents: a personal agent for every employee and service agents for your products.

Nabu is the Mesopotamian god of writing and scribes.

A personal agent for every employee

Its own memory, files and scheduled tasks. Each user's agent and sandbox run in their own pods, and connections use the user's own credentials.

Guardrails and a sandbox

Commands run in a sandbox with no capabilities and no cluster token. Administrators choose the models, the tools and the catalog; read-only connections expose only reading tools; every tool call is in the audit trail.

Built into your products

A product starts a service agent through an API or acts on behalf of a user. Its runner connects over an outbound WebSocket, so it needs no inbound port.

One agent across channels

The web, mail, Telegram and VK Teams lead to the same main conversation and the same memory.

A guide to installing Nabu on your own cluster is in preparation.

early stage

Hammurapi

A web platform that runs the product development cycle with an AI agent as a partner, from an idea to the value metric after release. Git stays the source of truth.

Named after Hammurabi, the Babylonian king known for his code of laws.

  1. Discovery

    • An idea or a problem becomes an issue
    • The agent works out its value and a metric
    • An expert accepts it into a feature
  2. Development

    • Specifications pass quality gates in order
    • The agent writes the tech and QA specifications
    • Code arrives as pull requests in every service
  3. Delivery

    • Merge and deploy
    • Feature flag and the value metric
    • Confirmation or one-click rollback

What a release teaches becomes the input of the next Discovery

More than spec-driven: every change is traced

Requirements have IDs, and a coverage matrix links them to services, test cases and pull requests. Every commit names its feature, task and initiator. Any edit returns a specification to draft, so an approval always covers the current text.

From research to production

One cycle covers the analysis of an issue, five specifications, code in every service, validation against CI results, the release and the metric that confirms its value.

People sign, the agent works

People accept issues, approve specifications, sign the validation and confirm releases. The agent acts within the user's permissions and has no delete tool.

Try the demo on your machine

A few minutes, Docker with Compose v2. No LLM key and no GitHub or GitLab account: the demo uses a built-in fake GitLab and a scripted agent.

git clone https://github.com/GreenOnGrey/hammurapi && cd hammurapi && ./install/install.sh --demo

Better together

Hammurapi uses Nabu in two ways.

Hammurapiproduct development cycle
  • The chat in Hammurapi is a window to the employee's personal agent in Nabu: the same conversation and memory.
  • The scenarios of the cycle, from issue analysis to code generation, run on Nabu service agents.
Nabuplatform of AI agents
  • LLMs
  • SKILLS
  • MCPs

Nabu gives agents the models, skills and MCP servers that your administrators connect.

In turn, the personal agent reads and creates issues in Hammurapi on behalf of its user.

What's next

A direction, not a feature list. None of this is in the products yet.

planned

Nabu

One place to analyse an employee's work communications: mail, messengers and the company's products in one agent.

planned

Hammurapi

The platform watches how the product works technically and proposes changes as new issues in Discovery.

Both products are at an early stage

Read the code, run the demo, open an issue and tell us what breaks. A star helps others find the projects.