Enterprise workloads infused with AI, Copilot, and automation across sales, service, and operations.
Learn moreEnterprise data platforms, modern app innovation, Azure infrastructure, and automated quality engineering.
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QA strategy, hands-on test engineering and test automation in Azure DevOps and GitHub, so your team ships on schedule and finds problems before customers do.
Where you are
Here's what we hear from engineering and product leads.
01
Regression testing takes a week, so releases either wait or ship untested.
02
Customers find bugs before your team does.
03
Test automation started once, broke, and nobody has had time to fix it.
04
AI features are shipping, and nobody is sure how to test them.
Our practice
none (approach and process)
A testing approach sized to your risk: what to test, how often, by whom, and what "ready to release" means for your team.
01
We rank features by business impact and test the ones that would hurt most first.
02
Release criteria everyone agrees on, so go or no-go isn't a judgment call at midnight.
Our practice
Azure Load Testing
Hands-on functional, performance, security and accessibility testing by engineers who know your product.
01
Scenarios built from how people really use your product, including the edge cases support hears about.
02
Performance testing before launch day shows how the system behaves at peak.
Our practice
Azure DevOps · GitHub Actions
Automated tests that run in your CI/CD pipeline on every change, so regressions show up in minutes instead of weeks.
01
Regression suites for the tests you run every release, kept small enough to maintain.
02
Flaky tests get fixed or removed, so a failed build means something.
03
Evaluation sets for AI features, so you know when a model or prompt change makes answers worse.
Need build and release pipelines too?
How we engage
One route from plan to production. Each stage tells you what happens next.
01
We learn how your business runs today, then agree on where to go and how to get there.
Engagements · Assessment
02
We prove it works on your data, then build it with your team and take it live.
Engagements · Proof of Value · Implementation
03
We keep it healthy in production, measure what changed, and plan the next climb.
Engagements · Managed Services
Capability examples
The kind of work this looks like. No client names until a story is approved.
Capability example 01
[EXAMPLE NEEDED: regression time]
[One line on a regression cycle we shortened, with the before and after.]
Capability example 02
[EXAMPLE NEEDED: automation]
[One line on a test automation suite we built in Azure DevOps or GitHub.]
Capability example 03
[EXAMPLE NEEDED: load or launch]
[One line on performance testing before a launch or peak event.]
Let's talk
Pick a time that works for you. We'll ask a few questions about your goals, then suggest a sensible first step.
Microsoft Solutions Partner · Data & AI (Azure) · Digital & App Innovation (Azure)