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AI and Machine Learning Services

45%
of organisations cite data accuracy or bias as one of the biggest barriers to AI adoption.

The real risk with AI isn’t that it fails. It’s that it appears to be working until it matters most.

Woman wearing VR headset
PRIYA 1

Priya couldn’t explain why the model made that decision

MARCUS1

Marcus couldn’t see the risk building across the data, model and live environment

Elena thought testing had already caught the bias

Elena thought testing had already caught the bias

ARJUN 1

Arjun still had no single view of whether the AI was ready to go live

Organisations are racing to adopt AI and machine learning to drive efficiency, automate decisions and unlock new value from data. But as AI becomes embedded into core systems, it introduces a new level of complexity.

What starts as innovation quickly becomes exposure. Because AI isn’t static.
It continues to learn, adapt and influence outcomes long after deployment.

Without the right controls, testing and governance in place, organisations risk making faster decisions, but with less certainty.

What if you could…

Machine learning@2x 3

Trust AI decisions with explainable, validated outputs aligned to real-world outcomes

Medical 2@2x 2

Identify risks early through continuous testing, monitoring and assurance

AI@2x 3

Improve data quality, reduce bias and build models on stronger foundations

Cloud@2x 3

Scale AI innovation safely without increasing risk exposure

Quality Engineering

Maintain control across the full AI lifecycle, from development to live operation

Our approach to AI testing services and quality assurance

We help organisations adopt and scale AI with confidence, combining advisory, quality engineering and continuous assurance into a single, joined-up approach.

From AI readiness assessments and use case design to implementation, testing and optimisation, we support the full lifecycle.

We design governed, scalable AI solutions, embed them into delivery pipelines, and apply independent assurance to validate performance, security, bias and compliance. Continuous monitoring ensures models remain reliable as they evolve.

We help you to deliver AI that is trusted, controlled and proven to deliver real business value.

Interpreting test diagnosis for 600 tests per day

How we can help

If you’re curious to find out more about our AI and Machine Learning services take a look at some of these pages:

AI engineering

End-to-end assurance that makes AI trusted, governed, and reliable across the full lifecycle, from data and model validation to continuous monitoring in production.

AI transformation

Using AI to accelerate and modernise testing, automating insight and diagnosis so teams deliver faster with higher confidence.

CASE STUDY

AI in software testing: Interpreting test diagnosis for 600 tests per day

A European telecoms/media provider ran thousands of automated Android Live TV playback tests daily. Even a small failure rate created significant manual triage, with engineers reviewing recordings, screenshots and logs and relying on specialist knowledge to pinpoint root causes across DRM, app updates and environment issues.

We added an AI analysis layer to a Test‑as‑a‑Service platform to automatically interpret device interactions, external video capture for DRM-protected playback and test artefacts (logs, timelines, screenshots).

The result: The system now analyses ~350–400 tests per day (scaling to 600) at ~95% accuracy, accelerating diagnosis and reducing manual effort.

User testing streaming application interface on television

Why Resillion for AI and Machine Learning?

Team@2x 3

700+ global experts

700+ specialists across quality engineering, testing and cyber security

AI@2x 6

End-to-end AI lifecycle coverage

Supporting AI from readiness and design through to testing, deployment and live operation

Technology@2x 3

AI-powered quality engineering

Using AI to accelerate testing, improve quality and expand coverage across the SDLC

Planning@2x 5

Independent AI assurance

Proven capabilities in bias testing, model validation, explainability and security testing

Goverement@2x 3

Trusted, regulation-ready AI

Supporting compliance with frameworks such as the EU AI Act and governance requirements

Medical 2@2x 3

Continuous monitoring and control

Continuous evaluation of models for drift, instability and real-world performance

VPN@2x 4

Data and model validation at scale

Testing data quality, bias and model behaviour across complex systems

Logistics@2x 2

Flexible delivery model

Advisory, implementation, testing or managed services aligned to your needs

Cloud@2x 4

Applied AI in complex environments

Delivering AI-enabled testing and assurance in large-scale, real-world systems

Robby Putzeys

Robby Putzeys

Head of Quality Engineering

Robby Putzeys is a seasoned leader with over 25 years of experience in software quality engineering, helping organizations deliver high-quality IT systems, digital products, and complex technology landscapes across industries such as telecommunications and consumer electronics.

Conor Thomson

Conor Thomson

Expert in Quality Engineering and AI Practices

Conor is a Global Solution Architect with 12 years’ experience in Quality Engineering, QA, test automation, software delivery, AI engineering, and digital transformation.