DevOps · Engineering, calmer

Ship without
flinching.

A deploy should not feel like rolling the dice. Cindy knows what your pipelines have done, what they are about to do, and what would happen if it went sideways. Routine deployments stay routine. The interesting ones get Cindy's full attention.

cindy · watching a deploy LIVE
01
A change went in
small commit · clean signal
DONE
02
Nothing alarming found
everything where it should be
DONE
03
Going out gently
a fraction of traffic, watching closely
EASING
04
A safety net is set
if the room turns, Cindy pulls it back
WATCHING
05
Will go wider if quiet
the rest, only when nothing complains
WAITING

Your delivery pipeline, finally working as one.

Every guardrail — across teams, tools, and pipeline stages — governed by one model.

60%
of the toil, handled by Cindy
Approvals, cost checks, and policy review run in one place on every deploy — so engineers build tomorrow's product instead of babysitting yesterday's.
“Shipped Friday. Actually took the weekend off.”
Same day
from PR-ready to PR-shipped
Approvals, security scans, and FinOps review run inline and in parallel — one governed path, one owner, no offline handoffs.
“Approved and shipped before standup.”
Every
check runs inside the pipeline
Policy, security, and cost gates evaluate on the change itself, before it ships — so the surprise gets caught in the pipeline, not two weeks later.
“The policy flagged it. Before it merged.”

Where the nerves usually live.

Most of what goes wrong in operations is not technically interesting. It is human, repetitive, and easy to miss. Cindy quietly watches the places where attention runs out.

Order, where there used to be guesswork

The shape of what you run, finally legible. You can point at it. You can move things around. Cindy knows what moved.

Pipelines that explain themselves

The stages, the gates, the conditions: visible, not buried. Where a policy applies, it shows itself. Where it does not, it gets out of the way.

Infrastructure by conversation

Describe what you want. Cindy drafts it, checks it against the rules, names what it will cost, and waits for your approval before anything is built.

Policies you can see

The rules that protect production aren't buried in a repo. They're visible objects — you can see what they guard, when they last fired, and why.

Security, inside the loop

Scans, checks, second opinions, folded into the same path your builds travel. Findings calibrated to where they actually live. Noise filtered before it reaches you.

When the world drifts, Cindy notices

The gap between what was declared and what's actually running — Cindy finds it first and stages the redeploy back to baseline, with an audit-ready record.

Outcomes an engineering leader measures

30–40%
faster release cycles, fewer rollbacks
0
manual handoffs; checks live in the pipeline
<5 min
mean time to revert, drift caught automatically
8→1
tools collapsed into the IDE workbench
Same delivery tools you already run. Every guardrail brought into the pipeline. Code to production, governed.

"Something feels off in production." Watch the quiet way Cindy handles it.

An engineer mentions a service is acting up. Three exchanges later, the drift is named, the redeploy is staged, the rollback is armed. Nothing dramatic. Nothing surprising. The way it should feel.

cindy · in conversation LIVE
> auth is acting strange in prod. what's going on?
[SEEING] auth and a few of its neighbors are running things that are not quite what your declaration says. Three other services have drifted in small ways too.
> show me all of it.
Seven services off baseline. [WHAT CHANGES] Auth touches three things downstream; they move back together. Plan staged. About four minutes. No downtime; it can be done rolling.
> approve.
[DONE] All seven back in line. Witness filed. The baseline is locked again. I'll keep watching for drift.
7
Drifted
4m
About
0
Downtime
What had drifted
auth · running a slightly older shapeversion
payments · pool sized differently than declaredconfig
checkout · scaled itself and stayed therescale
+ four moreview
Sovereignty by design
Our own purpose-built LLM, hosted in your data center.
Your data remains yours
Your code, pipelines, and configs never leave your perimeter.
Zero hallucination
Cindy answers operational questions from your own data, grounded in what is real.
Bring your own tools
Jenkins, GitHub Actions, GitLab, ArgoCD stay in place. EveryOps sits on top.

What EveryOps gives back.

DevOps · time returned

The engineering hours EveryOps gives back.

Move the dials. Cindy shows how much engineer time EveryOps gives back from drift, gate-keeping, and chasing what shipped.

in your browser
Your shape
Services in production 80
5100500
Deploys per week 40
550200
How often does drift surface?
Manual approval gates per deploy
Cindy
waiting
RESTING
Engineer-hours leaking per week
0h
Move the dials and Cindy will tell you
Drift archaeologychasing declaration vs. reality
0h
Manual gate-keepingapprovals, sign-offs, hand-offs
0h
Reconciling shipped vs. intendedwhat was supposed to happen
0h
Context-switching across toolsthe tax nobody measures
0h
Runs entirely in your browser Private to this session Directional estimate, not a quote

See EveryOps run on your operations.

You just watched the scenario. Book a demo and we will point Cindy at a slice of your real stack. You decide nothing until you have seen exactly what Cindy recommends.