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brainiac/studio

Digital Studio

brainiac/studiobrainiac/studio
← Infrastructure & DevOps
06 · infrastructure & devops / ci-cd

Ship on a Friday. Sleep on Friday night.

For teams where releasing an update means a whole afternoon, a shared checklist, and one nervous person. We automate the entire path — with checks that catch mistakes before your customers do, and a one-click way back if something slips through.

See our work
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our point of view

How long it takes to release a fix is the real speed of your company.

Ask a team how fast they move and they'll describe their roadmap. The honest measure is smaller: how long between someone fixing a bug and your customer having the fix. If the answer is two weeks and a meeting, everything else slows to match. Bugs queue up. Small changes get bundled into big risky releases. Releases get frightening, so you do fewer of them — which makes each one bigger and more frightening still.

Automating that path breaks the loop. Every change is checked automatically, goes out on its own, and can be reversed in seconds. Releases become small and dull. Your engineers stop dreading Fridays, your bug fixes reach customers the same day, and you find out whether an idea worked this week instead of next quarter.

<10 minFrom finished code to live, safely
10–30×More releases per month, typically
−80%Fewer releases that go wrong
what we build

What we build.

01

Automatic checks on every change

Before anything reaches your customers it's built, tested, and scanned for known security holes — automatically, in minutes. Nothing gets through on a promise that it's probably fine.

02

Releases at the push of a button

Or no button at all. Once a change passes its checks it goes live on its own. No checklists, no 'is anyone else deploying right now?', no staying late to babysit it.

03

An undo that genuinely works

Any release can be reversed in seconds, back to the exact version that was running before. We test the undo path too — it's the one you'll be using in a hurry.

04

Careful, gradual rollouts

New versions go to a small slice of your traffic first. If errors start climbing, the release stops and reverses itself before most people notice a thing.

05

A preview of the site for every change

Designers, marketers, and clients can click through a proposed change on its own private link and comment on it — before anyone approves it.

06

Passwords and keys kept out of the code

Stored properly, rotated on a schedule, and never sitting in a file someone can screenshot in a screen share.

07

Database changes handled safely

The scariest part of most releases. We make database updates run automatically in an order that's safe to reverse, so a structural change never takes the site down with it.

08

Four numbers your whole team can read

How often you release, how long it takes, how often something goes wrong, and how fast it's fixed. Enough to tell whether things are getting better — without a status meeting.

use cases

Who this is for.

01

Teams releasing once a month, nervously

Big releases are big risks. We turn one terrifying monthly event into twenty forgettable ones.

02

Engineering teams that grew fast

What worked with three engineers falls apart at fifteen. Automation is what stops everyone tripping over each other.

03

Agencies juggling many client sites

One set of pipelines that behaves identically on every project — so nobody has to remember how this particular client's site gets released.

04

Regulated businesses

When you have to prove who approved what and when, automated pipelines produce that record for free. No spreadsheet required.

approach

How we do it.

01

Measure

We time your current release path end to end: how long a one-line fix takes to reach a customer, how often releases fail, and where the waiting actually happens. It's rarely where people assume.

02

Design

We agree the pipeline on paper first: what gets checked, who approves what, which environments exist, and exactly what happens when something fails at 2am.

03

Build

We build it on one real service, prove it end to end, then roll the same pattern across the rest — so your team learns it once instead of four times.

04

Harden

Security scanning, gradual rollouts, a tested undo, and safe database updates. This is the part that makes the pipeline trustworthy rather than merely fast.

05

Hand over

Documentation, a training session, and time spent alongside your engineers on real releases until nobody needs us in the room.

06

Tune

We watch the four numbers for a month afterwards and trim the slow parts. A pipeline that takes 40 minutes gets used half as often as one that takes 8.

tech stack

Tools we use.

GitHub Actions
GitLab CI
Docker
Terraform
ArgoCD
AWS
Cloudflare
Node.js
PostgreSQL
pricing

Engagement models.

— 01

Starter Pipeline

from $10k

One application, one automated path from finished code to live — with tests, security checks, and a working undo.

  • One app, fully automated
  • Automatic tests and security scanning
  • One-click undo, properly tested
  • Documentation and a training session
Most popular— 02

Full Automation

from $30k

Several applications and environments, gradual rollouts, safe database updates, and a preview link for every proposed change.

  • Up to 5 services or applications
  • Preview link for every change
  • Gradual rollouts that reverse themselves
  • Safe, reversible database updates
— 03

Platform

from $70k

A shared setup your whole engineering team builds on, so every new service arrives with a working pipeline on day one.

  • Reusable templates for new services
  • Engineers help themselves, no tickets
  • Approval trail ready for auditors
  • Ongoing support retainer
faq

Frequently asked.

5 questions answered. Still have one? Reach out.

Often the pipeline exists but nobody trusts it — it's slow, it fails at random, and people quietly work around it. Repairing that is usually cheaper and faster than starting over, and we'll tell you honestly which one you need after a week of looking.

5 questions
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