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How it works

The architect leads. The team delivers.

Every request enters through the AI CTO, which decides what to build, by whom and in what order - then hands work to the engineer and DevOps agents, who check each other like a real company.

Join the waitlistHow it works

You say what the business needs. The architect decides what to build. The engineer builds it. DevOps ships and runs it. You make two decisions - and keep every key.

Operating principles

Four rules.Every agent follows them.

01

One head, one plan

Every request starts with the AI CTO, which decides what to build, who builds it and in what order.

02

Your permissions, always

You decide how far each agent may go. Defaults are careful, and only a person can widen them.

03

Undo-able first

Agents move fast on changes that can be reversed, and wait for you on the ones that cannot.

04

Nothing in the dark

Plans, decisions, code and changes are written down for you to read, approve and audit.

Who does what

The architect leads.The team delivers. You decide.

You

The owner

  • Set goals and limits
  • Approve budgets and go-lives

AI Architect & CTO

The head of IT

  • Understands your business
  • Checks what is feasible - and what is not
  • Picks the right tech for each stage
  • Directs the engineer and DevOps + SRE
  • Brings budgets to you for approval
  • Makes the call in an emergency - and explains why

AI Software Engineer

Builds it

  • Features, fixes and integrations
  • Tests and reviews on every change
  • Docs and pull requests

DevOps + SRE

Runs it on your platform

  • Releases, monitoring and on-call
  • Scaling, backups and security
  • Best practice by default

A new request

  1. 1You say what the business needs.
  2. 2The architect works out what to build, and with what.
  3. 3It directs the engineer to build and DevOps + SRE to prepare the platform.
  4. 4Finished code goes from the engineer to DevOps + SRE for release.

One request, end to end

Eleven steps.Two decisions are yours.

“We want online ordering with loyalty points before the summer season.”
A restaurant chain owner, before the summer season
Step
01 / 11
Owner approvals
0 / 2
  1. 1

    AI Architect & CTO

    Asks the questions a good CTO would: volumes, stores, systems, deadline, budget.

  2. 2

    AI Architect & CTO

    Reviews what you already run, with the access you grant.

  3. 3

    AI Architect & CTO

    Works out what exists, what is missing and what can be reused.

  4. 4

    AI Architect & CTO

    Tells you what fits the deadline - and what does not.

  5. 5

    AI Architect & CTO

    Hands you a one-page plan: cost, timeline and risks.

    You approve the plan and budget

  6. 6

    AI Architect & CTO

    Turns the plan into work for the engineer and DevOps agents.

  7. 7

    DevOps + SRE

    Sets up development, staging and production environments.

  8. 8

    AI Software Engineer

    Builds the ordering app, loyalty and POS sync - tested and documented.

  9. 9

    DevOps + SRE

    Ships to staging, runs the launch checklist, schedules go-live.

    You approve go-live

  10. 10

    DevOps + SRE

    Keeps it healthy, handles incidents and scales for weekend peaks.

  11. 11

    AI Architect & CTO

    Reports back monthly: cost, uptime, usage and what to do next.

The right tech at the right time

Built for today.Ready for what comes next.

Most teams over-build too early or patch too late. The architect picks what fits your stage - and changes it only when the business needs it to.

Prove it works - fast and cheap.

  • Architect decides

    A simple web app and a managed database. One environment. No over-engineering.

  • Engineer builds

    Builds a working prototype you can click through.

  • DevOps + SRE runs

    One-click deploys and basic monitoring.

Decisions you can follow

It makes the call.Then it tells you why.

If something breaks at 2 a.m. and nobody can be reached, the architect takes only the smallest step that can be undone. Then it explains the decision in plain words - so you are never left guessing.

Emergency decision · checkout

From your AI Architect & CTO · 02:14 AM

Resolved
What happened
Checkout errors jumped to 18% four minutes after release v2.4. DevOps + SRE raised it.
What I did
Rolled back to v2.3 - a step your settings allow without approval. Errors are back under 0.5%.
Why I didn't wait
You and your admin didn't answer for 10 minutes. Waiting another 30 would have hit around 2,000 orders. A rollback is fully reversible.
What happens next
The engineer has found the bug and opened a fix. It needs your approval before it goes back to production.
Keep it UndoAsk a question

Illustrative example

DevOps + SRE

Your platform, run by the book.Every day. Every night.

The practices strong ops teams follow - applied to your platform from day one, not after the first outage.

  • 01

    Everything as code

    Infrastructure and config are versioned, reviewed and repeatable - no hand-made servers.

  • 02

    Safe releases

    Automated checks before every release, gradual rollout, instant rollback.

  • 03

    Watched around the clock

    Monitoring and alerts on what your customers feel, not just what servers report.

  • 04

    Incidents, handled

    Contain first, fix the cause, then write it up so it does not happen twice.

  • 05

    Backups you have tested

    Regular backups and recovery drills - because an untested backup is a hope.

  • 06

    Patched and locked down

    Updates, secret rotation and access reviews on a schedule.

  • 07

    Cost under control

    Idle and oversized resources found and fixed every month.

  • 08

    Clear service targets

    Agreed uptime and speed goals, tracked and reported to you.

Meet DevOps + SRE

Watch one request

Say what you need.The team takes it from there.

Trust & control

Agents act.You decide how far.

Set an autonomy level for every kind of decision, per environment and budget. Prompts never grant permission - only a human can raise a level.

L2

Act with approval

Go ahead once the right person says yes.

For example

Release a new version to production.

  • Scoped by environmentDev, staging and production each get their own level.
  • Scoped by money and timePer-action and monthly caps; business hours or always.
  • Irreversible waits for youDeleting data, IAM changes and contracts always need a named human.

The platform underneath

Built once.Every agent runs on it.

Shared agent runtime

Coming soon

Every agent shares one engine, so every improvement reaches all of them at once - and new agents arrive fast.

  • Long jobs, no restarts

    Big work keeps going - and can wait for your approval - without starting over.

  • Remembers your project

    Your stack, decisions and history, recalled when they matter.

  • Right model for the job

    Each task goes to the model best suited to it. Quality up, cost predictable.

  • Plugs into your tools

    Your cloud and your tools, connected - and open to your own agents too.

Explore the runtime

Governance & control plane

Coming soon

An agent that can change production is a privileged user. We treat it exactly like one.

  • Only the access a task needs
  • Every action checked against your rules
  • Agent code runs in isolation
  • A complete, exportable record
  • Spend limits agents cannot cross
  • Instant kill switch
See the controls

Getting started

Three steps.No hiring round.

  1. 01

    Tell it what you need

    In plain words, the way you would brief a CTO. The architect asks the questions a good one would.

  2. 02

    Set how far it may go

    Pick an autonomy level per decision and environment. Approve the plan and budget when it asks.

  3. 03

    Watch it ship and run

    Pull requests, releases and incidents arrive as reviewable artifacts - with a monthly report on all of it.

Hire your AI IT company.Before your next hire.

Early access opens to a small group first. Tell us what you would hand over, and we will be in touch.

Join the waitlistHow it works