These are the problems I get called in to solve. They sit at the intersection of engineering, leadership, and organisational design. If you are looking for someone to run a test cycle, this is not the right page.
Most organisations do not have a testing problem. They have a capability problem that shows up in testing. Regression cycles that take weeks. Automation that covers the wrong things. Test data that blocks releases. Teams that are busy but not effective.
This is the work I have done most at scale: restructuring how quality engineering operates across large, complex organisations. That means redesigning the operating model, rebuilding automation capability, fixing test data management, and doing all of it across multiple geographies at the same time.
Quality problems that persist across multiple programmes usually have one thing in common: nobody with real authority owns them. Testing gets treated as a delivery function rather than a strategic capability. The decisions that shape quality, including resourcing, risk tolerance, and release thresholds, get made by people who are too far from the consequences.
This practice area is about changing that. Building the governance model that puts quality decision-making where it belongs, at the leadership layer, with clear accountability and the right visibility for the people who need it.
Testing AI systems is not the same as testing software. The inputs are probabilistic, the outputs are non-deterministic, and traditional pass/fail test cases often tell you nothing useful. Organisations deploying AI in production are discovering this the hard way.
This area covers the full scope of what it means to properly test and govern AI systems: from bias and fairness validation during development through to drift monitoring and evaluation strategy in production. The AQ ELEVATE framework provides the structure for doing this at enterprise scale.
Tools and processes do not transform testing capability. People do. This area is about building the internal structures that develop people: communities of practice, learning programmes, mentoring frameworks, and the cultural conditions that make quality a shared responsibility rather than a QA team problem.
The Test Chat, the global community I founded and lead as Chief Enablement Officer, is the public expression of this belief. The internal equivalent, built for a specific organisation, is what this engagement type delivers.
Conference keynotes and executive panel moderation on QE transformation, AI quality, and leadership governance. Built for audiences who are tired of the same talking points.
Strategic advisory for CTOs and VPs navigating quality transformation, AI governance, or testing operating model design at the executive level.
End-to-end QE transformation programmes delivered through Infosys. TMO and TCOE restructuring, automation scaling, and multi-geography operating model design.
Half-day or full-day structured sessions for leadership teams on quality governance, AI quality strategy, and building a trust-centric quality culture.
Most conversations start with a 30-minute call. No obligation, no sales pitch.