First dedicated customer deployment live, July 2026

AI Employees

Cognitive Companion

In development Does the work of a whole team of specialists

Your people and your AI agents in the same room. Chat, voice, and video with shared memory, on your infrastructure or your own device.

Private instances only. Each org gets its own isolated stack and SSO.

Your people + agentsRooms with voice, video, and canvasShared memory on your stack

Who it is for

A private thinking partner for long-horizon work.

Teams who want agents working beside them in real rooms, not bolted on as a chatbot tab: founders, ops teams, and orgs that want the whole thing running on infrastructure they control.

Why it wins

Depth over chat theater.

01

Stop copy-pasting context into a chatbot. The agents are already in the room, and they already know the thread.

Puts humans and AI agents in the same rooms as equals: agents answer in chat, stream replies live, join voice and video calls, hear you through local Whisper transcription, and remember the conversation.

02

One question, many minds: a whole panel of models or a bench of 35+ specialists, without leaving the conversation.

Fans hard questions out on command: /council polls a diverse multi-model panel in parallel and posts one synthesized answer; /facilitate hands the turn to the best of 35+ specialists, who answers in-room; /research routes to Center Deep for a cited multi-source report.

03

Your rooms, your data. Every deployment is a single-tenant stack with its own database and org-scoped SSO, and there is an on-device mode that runs local models on your own machine.

Keeps the memory: per-room and fleet-wide knowledge bases with citations and a readable document viewer, agents that search them and write learnings back, plus a canvas pane for HTML, SVG, Mermaid, React, and sheets with version diff.

How it works

Load context. Think with it. Keep the thread.

01

Get your own instance

We provision your org its own isolated instance: dedicated Postgres, Redis, and LiveKit, wired to your SSO, in one command on our side.

02

Fill the room

You create rooms, attach knowledge bases, and invite people and agents. Agents read the room's knowledge, cite it, and add what they learn back.

03

Work out loud

Work happens in the open: live calls with real-time transcripts, council panels, delegated specialists, scheduled research monitors posting into channels, and cross-room search over all of it (Cmd+Shift+F).

Screenshots

Product tour coming soon.

Room view with an agent streaming a reply while two teammates and a specialist agent share the channel

Product capture coming: Room view with an agent streaming a reply while two teammates and a specialist agent share the channel.

Live voice call with real-time transcript and an agent on the line answering from the room's history

Product capture coming: Live voice call with real-time transcript and an agent on the line answering from the room's history.

/council result: one synthesized answer with the multi-model panel and knowledge-base citations visible

Product capture coming: /council result: one synthesized answer with the multi-model panel and knowledge-base citations visible.

Proof and access

What's proven today.

35+specialist agents on call via /facilitate
6/6model lanes verified, local and cloud
~1.6slocal agent loop on-device

Proof points

  • We run Magic Unicorn on it every day: standups, voice calls with agents on the line, research monitors posting into channels.
  • Our first dedicated single-org customer deployment went live in July 2026 on its own isolated stack with org-scoped SSO.
  • 35+ specialist agents routable through orchestrator delegation, and all 6 model-switcher lanes verified routing across local and cloud models.
  • Before launch we ran a 40-agent adversarial security audit against it, then fixed and end-to-end verified every in-app blocker it found.
  • The on-device companion runtime runs today on an AMD Strix laptop and a Mac Studio: local Qwen models, a temporal knowledge-graph memory, and a ~1.6 second local agent loop.

Pricing and access

We run our own company on it every day, and the first dedicated customer instance is live now. There is no self-serve signup: every deployment is a private single-tenant instance we provision per org. Follow the build log to watch it open up.

Shipping log

What just shipped.

  • July 2026: first dedicated single-org customer deployment went live on its own isolated stack
  • July 2026: /research wired to Center Deep, with scheduled research monitors posting cited reports into channels
  • June 2026: /council multi-model panels, orchestrator delegation across 35+ specialists, global cross-room search, and web-push notifications shipped

FAQ

Plain answers.

Is this Unicorn Commander?

No. Unicorn Commander is the infrastructure control plane that runs models and routes inference. Cognitive Companion is where your people and your agents actually work together, and it runs happily on top of it.

Can agents really join a voice call?

Yes. Calls run on a LiveKit stack with local Whisper transcription, so agents hear you in real time, answer on the call, and pick up the text conversation the room was already having.

Can I sign up today?

Not self-serve yet. Every deployment is a private single-tenant instance with its own database and SSO, provisioned per org. Email us and we'll talk about an instance for your org.

Does it run on my own hardware?

The hosted product deploys as an isolated stack per org, on infrastructure you control if you want. There's also an on-device companion runtime with local models, file indexing, and knowledge-graph memory; it runs on our own AMD and Apple machines today and federates into the hosted fleet when online, but it's not a packaged download yet.

Which models does it use?

Both local and cloud. You can switch models mid-chat across 6 curated lanes, and everything meters through one gateway so usage stays visible and predictable.