Service · Quality Engineering & Performance
Tests on the paths that cost money
Chasing a coverage percentage is expensive and proves little. We test checkout, quoting, invoicing, login, and whatever else stops revenue when it breaks, then fix the pages people wait on.
- Test scope chosen by business impact, not by file count
- Every check runs on each deploy, and blocks a bad release
- Performance measured on real devices and real connections
- A failing test names the broken flow in plain language
What you get
Deliverables, not slideware
- 01
Critical path list
The flows that lose money or trust when they break, ranked, agreed with you in writing.
- 02
Automated suite
End-to-end checks on those flows, running on every deploy and blocking bad releases.
- 03
Performance baseline
Load times measured before and after, on the pages your users actually wait on.
- 04
Regression report
What broke, when, and which change caused it, in language a non-developer can read.
- 011. quote → accept → invoice covered · runs on deploy
- 022. customer login + reset covered · runs on deploy
- 033. payment webhook retry covered · nightly
- 04p95 load: 4.1s → 1.3s on the quote screen
- 05releases blocked by red check: 3 this quarter
How it runs
What actually happens, step by step
No discovery theatre. Each step ends with something you can read or use.
- 01
Rank by impact
Which failures cost revenue or trust today.
- 02
Automate those first
End-to-end, on real flows, on every deploy.
- 03
Measure the wait
Real devices, real connections, before and after.
- 04
Block bad releases
A red check stops the deploy, not a person's memory.
Tangible
What lands in your hands
Named objects with a format and a week attached, so the handover is easy to picture.
Working automation
One process running end to end, on your data, with a human approval step.
Deployed servicePhase oneOperating runbook
What to do when it fails, who to call, how to roll back.
PDF · 8 pagesFinal weekEvidence dashboard
The numbers that prove it worked, refreshed daily.
Live URLWeek 5Source repository
Yours from day one, including the prompts and the evaluation set.
Git repo + READMEWeek 1
Operating Runbook
Failure modes, rollback steps, and who owns each alert.
This is the real template, with client figures replaced by representative ones. Read it before you talk to us — if the format is not useful to you, the engagement will not be either.
Before and after
What the change looks like in the week
Red is the cost you carry today. Green is what the system gives back.
Today
- Releases are followed by a nervous afternoon
- The same bug returns every few months
- Slow pages are known but never measured
- Customers report failures before you see them
After
- The money paths are checked on every deploy
- A returning bug is caught by the test that found it first
- Load times measured, with a before and after
- Failures surface in your alerts, not in an email from a client
Objections
Answered before you ask
Do you aim for 100% coverage?
No. Full coverage costs more than it returns for a company your size. We cover the flows where a failure is expensive.
Can you test software we did not build?
Yes. End-to-end checks work against the running application, so we do not need to have written it.
Is performance work separate?
It is usually the same engagement. Once the critical paths are automated, the same paths are the ones worth speeding up.
Keep going
Where people look next
Related work, the category this sits in, and the proof behind it.
One next step, and it is a paid one on purpose
The AI Opportunity Diagnostic is a fixed-scope engagement. You leave with a ranked plan you can act on with us or without us.
Still sizing the problem? Write to us in your own words first. A person reads it.