AI and Machine Learning Operations
Run AI with confidence and control
AI models can drift, degrade and introduce risk once they are in production. Resillion’s AI/ML Ops offering helps you manage deployment, monitoring, explainability and ongoing assurance throughout the model lifecycle. This helps you to reduce operational risk and scale AI with confidence.
Independently recognised and accredited
Our accreditations and certifications show our commitment to recognised standards for quality, security, testing and assurance.
Keep AI controlled and continuously assured
Our AI/ML Ops offering covers training, retraining, deployment, measurement and production monitoring. This helps you manage models as live operational assets, rather than one-off technical projects.
We combine AI operations, quality engineering, explainability, open-source assurance tools and practical governance to help you stay in control as models change.
Our tool-agnostic approach builds assurance in from the start. We select tools that fit your development environment, delivery model and risk profile, helping you operate AI reliably as it scales.
Governance that connects policy, controls, testing and monitoring
Our GRC approach works across your AI landscape with machine learning, generative AI, and AI embedded in products, platforms, and delivery processes. We connect four essentials:
- Clear ownership and accountability
- Policies, standards, and control frameworks
- Continuous testing and assurance
- Real-world performance and risk monitoring
By building assurance into the whole AI lifecycle, governance becomes a living system that keeps up with the evolution of AI within your business. You’re able to reduce risk while providing the evidence needed to keep the regulators, auditors and board happy.
As part of our Total Quality approach, GRC brings both governance and real-world assurance together, linking defined controls with continuous testing, monitoring, and validation. The result is measurable, audit-ready evidence – from reports and metrics to traceable logs – giving you the confidence to show that you’re compliant and in control.
BENEFITS
How Resillion’s AI/ML Ops offering gives you stronger control over live AI
At Resillion, our approach to delivering AI/ML Ops offers advantages such as:
Clearer visibility across your live model lifecycle
Earlier detection of drift, degradation and risk
Greater confidence in how your models behave
Stronger alignment between AI operations and governance
Less fragmentation across tools, teams and controls
More scalable AI adoption with continuous assurance
Challenge
A leading telecommunications and media provider was running thousands of automated Android Live TV playback tests every day. Even a small failure rate created heavy manual triage, with engineers reviewing recordings, screenshots and logs to identify issues across DRM, app updates, account changes and test environments.
Approach
Resillion enhanced its Test-as-a-Service platform with AI-driven test result analysis. The solution automatically analysed recordings, screenshots, logs and timelines, then surfaced step summaries, detected error messages, evidence, timestamps and side-by-side comparisons to help teams understand what happened and why.
Result
The system now processes 350 to 400 tests per day with 95% accuracy, helping the client identify root causes faster, reduce manual effort and improve confidence in high-volume validation.
WHY US?
How we turn capabilities into results
Here’s how our AI/ML Ops offering delivers positive business outcomes:
Lifecycle operations
What this does for you
You manage training, retraining, deployment and measurement consistently
Result
More controlled AI operations
Production monitoring
What this does for you
You track drift, degradation and live model behaviour
Result
Earlier risk detection
Model explainability
What this does for you
You understand how models behave and why
Result
Greater confidence in AI decisions
Drift detection
What this does for you
You spot performance changes before they escalate
Result
More stable model performance
Open-source assurance
What this does for you
You avoid rigid tooling and vendor lock-in
Result
Greater operational flexibility
Quality engineering integration
What this does for you
You align AI operations with existing QA and QE practices
Result
Stronger delivery consistency
Governance controls
What this does for you
You keep oversight, accountability and evidence connected
Result
Better audit readiness
Continuous validation
What this does for you
You keep assurance active as models and data change
Result
Sustained confidence over time
WHY NOW?
Still hesitating? See what’s at stake
If you’re not convinced by Resillion’s AI/ML Ops offering, consider what you’ll be up against without it:
Production models can fail silently as real-world data changes
Unchecked drift can weaken decisions before teams notice
Fragmented tools can make ownership and accountability unclear
Manual monitoring can slow response to emerging model issues
Poor evidence trails can make governance harder to defend
Isolated AI initiatives can become difficult to scale safely
Our Experts
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.
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.
