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Quality Engineering & Testing

Bugs cost less on Tuesday than in production.

Full-stack practice

Test automation, AI-powered QA and performance and security testing built into delivery, not bolted on before release.

Let's Build Together →

Why it matters now

$2.41T
annual cost of poor software quality in the USCISQ, 2022

CISQ estimated poor software quality cost the US economy $2.41 trillion in 2022. AI-generated code makes the problem bigger, not smaller: more code, faster, reviewed less. Manual regression testing can't keep up, and teams either slow releases down or ship and hope. Quality has to be engineered into the pipeline.

What changes for your business

  1. 01Release confidence without manual regression marathons
  2. 02Defects caught where they're cheapest to fix
  3. 03Performance and security proven before customers test them

What this covers

  1. 01Test automation & continuous quality engineeringEvery commit tested. Every release boring.
  2. 02AI-powered quality assuranceLet AI write the tests. Let engineers judge them.
  3. 03Performance, security & compliance testingFind the breaking point before your customers do.

Diagnose. Prove. Ship. Run.

Four stages, each with an exit. Stop after any one of them and you still walk away with something that works.

  1. 01

    Diagnose

    Typically 2–4 weeks

    We map the problem, your data and your systems, and agree the one number that defines success.

  2. 02

    Prove

    Typically 4–8 weeks

    A working pilot on your real data, measured against that number. Not a slide demo.

  3. 03

    Ship

    Scoped to the outcome

    Production build with security, monitoring, cost controls and documentation included, not upsold.

  4. 04

    Run

    Ongoing, optional

    We operate what we built against clear service levels, or train your team to. Your call. No lock-in.

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