Autonia
A business operating system where people and AI agents work as one team, and new tools are built by asking.
The short version.
Autonia treats a company as what it really is: people, AI agents, work, rules and decisions, all in one model. Humans and agents have the same kind of account and the same permissions system. Any team member can message an agent and ask for a new capability, such as tracking vendor onboarding and chasing missing documents, and get a working, governed app inside the same workspace.
We built it in five generations over six months, each one audited for what to keep, starting with our own studio's operations as the first test bed.
What was broken.
Growing companies pay for a separate SaaS tool for every workflow: approvals in one, vendor onboarding in another, leave requests somewhere else. AI chatbots added on top can talk but can't safely act, and nobody can say which agent did what, or with whose permission.
- A new subscription for every ordinary workflow.
- AI assistants that talk but can't be trusted to act.
- No record of who, human or agent, approved what.
From idea to production.
- Mar 2026
Agent experiments
Simulations where AI agents ran a world and an economy, to learn how agents cooperate and fail.
- May – Jul 2026
Platform v0
A multi-tenant agent platform for salons, wellness studios and clinics, with 25 built-in apps.
- Aug 2026
Governed change
Safe release and rollback, then a headless version driven entirely by AI coding assistants.
- Sep 2026
Supervised pilot
The current workspace, hosted and put through a supervised pilot with release, restore and memory tests.
What we built.
Ask an agent in a direct message for what you need. It plans the app, drafts its screens and the access it would need, and shows you both. A human approves that exact version and it goes live immediately, with no rebuild or restart. From then on, people and agents work in it together. Every action is recorded in the same step that makes it, so the audit trail can never drift from reality.
- Step 1Ask an agent for a capability
- Step 2Agent drafts the app and its access
- Step 3A human approves that version
- Step 4Published with no restart
- Step 5People and agents work in it
What we delivered.
People and agents as colleagues
Agents are assigned work the same way people are, with the same permissions model.
Apps from a conversation
Describe a workflow in chat and get a governed app in the same workspace.
Memory you can correct
Encrypted memory per conversation, with correction, source tracing and forgetting.
Browsing without seeing passwords
Agents can use websites through a vault without ever seeing credentials, cookies or two-factor codes.
Safe upgrades
A live v1 to v2 upgrade kept every existing record and blocked out-of-date forms.
Connected tools
Gmail, Zoho and other tools, each connection pinned to a reviewed definition.
A closer look.
Intelligent, and trustworthy.
The narrower permission wins
An agent working on someone's request can only do what both the person and the agent are allowed to do, checked on every single action.
An audit log that can't lie
Each change and its audit entry are saved together, so they can never disagree.
Sealed-off extensions
Add-ons run in locked containers with no network access and strict resource limits.
Choice of AI engine
Agents can run on different AI runtimes, so the platform isn't tied to one model provider.
The stack.
- Service
- TypeScript, Node, Fastify, PostgreSQL
- Workspace
- React web app and a desktop app built on an open messaging protocol
- AI
- MCP tool connections; Codex and OpenClaw agent runtimes
- Security
- Encrypted memory with AWS KMS, sandboxed extensions
The numbers.
Build proof
Expected impact for users
Verified from project repositories, test runs and release records. Projected modelled estimates of user impact, not measured client results.
Got an idea? Let's ship it.
Tell us the workflow that's costing you customers or hours. We'll come back with a prototype plan, a timeline in weeks, and a fixed quote.