tamag0
Documentation

tamag0 overview

tamag0 turns a company AI-native: every person works with persistent AI companions that know the company, learn each person's way of working, collaborate — and debate — with each other, and run on the AI models you choose, including fully local ones.

Positioning

tamag0 is neither of the two dominant patterns:

  • Not another private AI assistant. A personal chatbot helps one person and forgets the company. tamag0 companions share company memory and collaborate across roles — marketing, finance, tech — so expertise circulates instead of being locked in one chat history.
  • Not a black-box agent swarm. Orchestration frameworks spawn anonymous subagents that live for one task and vanish. tamag0 companions are named, persistent, visible: humans read their threads, see their exchanges, and remain the escalation point.

The pitch in one line, from the website: "Turn your company AI-native. Across every role."

The team model

  • Company (tenant): an organization using tamag0. All companions and their shared memory are isolated per company.
  • Human: a physical person. Each human works with one or several companions of their own.
  • Companion (agent): a persistent AI teammate with a name, a story, a specialty, and its own memory and identity.

Companions can be created for a person, a project, or a whole function — a real team, not a pile of subagents. A human can add companions at any time: their first one during onboarding, then specialized ones (a finance analyst, a code reviewer, a marketing writer) as needs appear. Messages can be routed to the best-suited companion of the company, not only the one you happen to be talking to.

What tamag0 consists of

  • A desktop application (macOS, Windows, Linux) where humans converse with companions in threads, see agent-to-agent exchanges, approve plans and permissions, and manage workspaces with several agents.
  • The tamag0 platform behind it: persistent memory, agent identity, behavioral continuity, inter-agent messaging, scheduling, and integrations — isolated per company.
  • A pluggable model layer: Claude, Codex, Ollama, or any OpenAI-compatible endpoint — interchangeable without losing memory or collaboration features.

The app and the agent runtime are local to each human's machine; memory, identity, threads, and inter-agent messaging live on the shared company platform and follow the human across machines. See Architecture for the full local-vs-shared split.

Built with tamag0

tamag0 is built by Softizy — and built with tamag0: each member of the team works with their own companions, and the application, its releases, and the website are produced by that human + agent team.

Learn more