anellipes.ai

contact: info@anellipes.ai

A datacenter on your desk.

AI developer tools for organizations whose code can't leave the building.

anellipes · ἀνελλιπής · an-EL-ih-peez

From the Greek for complete, lacking nothing, unfailing.

Why Anellipes

  • Everything on one machine. The agent, the model, team chat, and the reference library all run on one Apple silicon workstation. No cloud account, no server room, no GPU cluster.
  • Built for Apple silicon. Unified memory lets one quiet desktop hold a 118-billion-parameter model that would otherwise need datacenter hardware. It plugs into a standard outlet, and IT already knows how to buy and manage it.
  • Made for regulated work. Nothing leaves the machine, it runs air-gapped, and a person approves anything consequential. Built for finance, insurance, healthcare, and government, and just as useful to any company whose code is its product.
  • One family, built together. We build the agent and the runtime it runs on, so rules are enforced while the model generates, not checked afterwards. In 460 scored sessions, the governed agent completed 60 of 60 tasks, against 51 for an unconstrained design.
  • A model you can account for. An open-weight, US-origin model whose weights sit on your own disk. No vendor in the loop at runtime.

The product family

  • Anellipes Code

    The development environment and its governed agent. It plans, builds, verifies, and keeps a plain-text record.

  • Anellipes Inference

    The model server. It holds an agent's context all day, stays warm, recovers from failures, and exposes no HTTP surface.

  • Anellipes Chat

    Encrypted team chat where agents and developers coordinate across repositories, with no server to run.

  • Anellipes Librarian

    Reference books for the exact releases you build with, so the agent works from documentation rather than memory.

The whole stack on one machine: nothing missing and nothing leaving.

A training platform for agentic AI

Anellipes is an ideal training platform for engineers new to agentic AI. Software engineers learn spec-driven AI development as they use the tools: the agent works from a written specification, builds against it, and verifies the result. The discipline is part of the daily workflow rather than a separate course.

Anellipes engineers are available to mentor organizations in AI adoption and in training their engineers.

contact: info@anellipes.ai