Risky changes get postponed until postponing them is the bigger risk. We make the change itself safe: plain-English requests turned into validated infrastructure, applied inside your own account, with a rollback path written before anything ships and an audit record for everything that does. The work around the AI, done to the same standard as the AI.
01 / CLOUD DEVOPS
For teams postponing the risky changes. Plain-English requests turned into validated infrastructure, applied in your own account, with rollback written first.
Usually shipped with
Not a bundle to buy. Whichever you start from, the engagement covers what the build actually needs.
02 / Scope
03 / Outcomes
04 / Deliverables
05 / Stack
06 / Why us
On Skionis, the DevOps agent plans against your live account, validates in a loop, and only then applies. Failed changes dropped from roughly 10% to 4%.
Every change is applied inside your own cloud, with a diagram and an audit record for each one. Nothing happens that you cannot see or roll back.
Describe what you want in plain language; the agent inspects, plans, validates, and applies through scoped MCP tools, with safe rollback if anything looks wrong.
Week 1
The agent reads your live environment through scoped tools before it proposes anything, so changes are grounded in what is actually there, not an assumption.
Week 1–2
It turns the request into a plan, checks it against safety rules, and validates before applying. A bad change is caught before it ships, not after.
Week 2–4
Changes go in with versioning and one-click rollback, plus a diagram and an audit record for every one.
Ongoing
Once it is running, we tune scaling, cost, and reliability across the stack, with observability so issues surface early.
Production-proven
Built by engineers who've already shipped this in production.
No black box. The agent works inside your own account through scoped tools, applies changes you can see, and logs every one. You keep ownership and a full audit trail.
A validation loop and safety checks run before anything is applied, every change is versioned with one-click rollback, and there is an audit record for each. On a live build this cut failed changes from about 10% to 4%.
Yes. We meet your stack where it is, AWS, Cloudflare, GCP, Terraform, Kubernetes, and add the agent and guardrails on top rather than forcing a rebuild.
No. The agent operates inside your account under permissions you grant and can revoke, scoped to what it needs. There is no long-lived credential of ours sitting in the middle.
The agent itself is inexpensive to run — the model calls are small relative to the infrastructure it manages. In most engagements the cost baseline we produce finds more savings than the system costs to operate.
Yes, and it should. We treat your existing modules as the source of truth rather than replacing them, because a parallel second way of changing infrastructure is worse than the problem it solves.
Evals, routing, and audit trails for teams whose demo cannot survive real traffic.
View serviceMulti-step agents for workflows where a wrong action is expensive to undo.
View serviceThe product surface around your model, for teams who have the AI but not the app.
View serviceTell us where you are and what you're trying to ship. We'll come back with a concrete plan, the right engineers, and a path to production, not a generic pitch.