Software Company Engineering and AI QA

Software companies

Your roadmap grows faster than your team. AI code ships faster than QA.

Customers expect a release every few weeks, and senior engineers take months to hire. AI tools write more of the code, and fewer people test it. Perform puts senior engineers and AI QA engineers on your product team, working your hours.

Three ways to start
01Senior engineers on your product teamEngineers in your repo and your standup, each screened by a Perform engineer.
02Tests for AI-written codeRegression checks and quality gates on what your AI tools write, before it reaches a customer.
03QA for your AI featuresWe question your AI features the way your customers do and show where they go wrong.

The release date holds. The test plan does not.

AI tools let a small team write a lot of code. The test plan was written for the old pace.
Bugs that used to show up in QA now show up in a customer’s account, and the support team hears first.
Meanwhile the senior roles that would fix it stay open for months.
We add senior engineers who build with AI and test what it writes, inside your review process, so the release pace and the quality bar both hold.

How a change reaches your customers

With quality gatesEvery AI-written change
Reviewed by a senior engineerRegression tests run
Released ✓Bugs caught before customers see them
Without themAI-written change, quick review
Passes the old test planBreaks in production
✕
Found by a customerThen traced back by hand
What we build

Every change goes through the same checks, in the tools your team already uses.

We follow one change, then build the first check.

An engineer sits with your product and QA teams and follows one change from ticket to release. We pick the step where bugs slip through, build the check into the tools you already run, and stay after launch, because month two is when the real exceptions show up.

Senior engineers on the roadmap

Engineers who join your standup and your repo, and most stay for years.

Tests for AI-written code

Regression suites and quality gates on the code your AI tools write.

QA for AI features

Your AI assistant questioned the way customers use it, with every answer that breaks your policies shown.

Engineers who stay past launch

The same engineers through month two and three, when the exceptions start showing up.

Results from two systems that could not go down

One is a software platform and one is an SAP program. What carries over is the handover. The team running the system afterward works for you.
One reservations platform: the concurrent user ceiling went from under 100 to 1,000, and the opening rush now clears 3,500 reservations in 10 minutes.
CommScope: 72 SAP test cases converted, double the requested load proven, and the testing capability handed to their team.
You can take the read and stop there. Some do.

Your team can name the release that worried them.

We bring engineers who build with AI and test what it writes, inside your review process.

Nobody agrees on what to build first.

More candidates than you can fund. 2 to 4 weeks on one problem, ending in an order of work and a first piece scoped.

Questions about product engineering work

Will your engineers work in our stack and our process?

Yes. They work in your repo, your review process and your definition of done, and you interview each one before they start.

Who checks the code our AI tools write?

A senior engineer reads it, tests it and answers for it. We add regression checks and quality gates where bugs have slipped through before.

Where are your engineers, and what hours do they work?

They work from LATAM, India and the Philippines, on your hours, in your standups.

Start with a conversation

Your team knows which release worried them. We follow one change from ticket to release, then name the first check to add.
Where AI-written code enters your release process
Which parts of the product have no regression test
One check named first, with what it protects