PRACTITIONERS IN IT QUALITY, RISK & ASSURANCE
Trust in Technology.
Confidence in Change.
For firm reliance on the digital estate running your enterprise — and on the AI reshaping it.
What We Do
Capabilities & Practices
Capabilities
Information Technology Test & Risk Assurance Capabilities
A structured framework for the quality and test function — governance, delivery, oversight and exceptions — built to work across a whole portfolio rather than one project at a time.
Quality & Test Governance · Test Delivery Management · Test Exceptions Management · Quality & Test Oversight
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Practices
Artificial Intelligence Solutions Testing & Assurance
A standards-driven reference model for assuring AI — from first assessment through to a practice with the standing to hold AI to account as it scales.
ASSESS · BUILD · PROVE · FORMATION
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the Continued Case For Assurance
What's Changed? What Hasn't?
1. Delivery became a portfolio
Technology delivery stopped being a sequence of projects. It became a portfolio — parallel change, layered dependencies, and investment that no longer has a completion date.
In Deloitte's 2025 Tech Value Survey of nearly 550 technology leaders, digital-initiative budgets rose from 7.5% of revenue in 2024 to 13.7% in 2025.
2. Assurance stayed project-shaped
Testing is still organised largely project by project, each one proving its own case and none of them proving the whole. Quality appears acceptable everywhere it is measured, and risk accumulates where nobody is measuring.
The Institute of Internal Auditors' Risk in Focus 2026, surveying over 4,000 practitioners across 131 countries, found digital disruption rated a top-five organisational risk by 48% — but a top-five audit priority by only 32%.
3. Then AI arrived
Systems that keep changing after release, whose behaviour was never fully specified, and whose failures do not announce themselves as defects. The gap is the same shape. Closing it takes something the existing toolkit does not contain.
McKinsey's 2025 survey found 47% of organisations had already experienced at least one negative consequence from generative AI, while only 27% reviewed all AI-generated output before use.
The question hasn't changed: Can this technology be relied upon? What's changed is whether anyone can still answer it.
One gap. Two frontiers.
Why TAL?
Structured By Standards. Shaped By Delivery.
Modular by design
The frameworks are built as components, not packages. You take the capabilities you are missing and leave the ones you already run well. Nothing here requires you to replace a methodology, a toolset or a supplier before you can start.
Practitioner-led
Both frameworks were built by people who had to make delivery work, not by a methodology team writing for other methodology teams. Every practice, process, enabling activity, and deliverable in them exists because its absence caused a real-world problem that someone had to solve at the time.
Ours to develop
iT-TRAC® and AISTA® are both registered marks, developed in-house rather than licensed or adapted from a vendor methodology. When practice moves, we change them. When they are used on your work, we are answerable for them.
Assuring quality since 2013.
Enablement
Expertise Alongside Your Team
Some problems need a full engagement. Others need someone experienced to sit with the people you already have, at the intensity the situation actually warrants, or sometimes a classroom-based environment to help educate, orient and prepare your staff.
Our programmes encompass one-to-one coaching, in-situ team guidance and knowledge transfer, as well as targeted training sessions.
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Outcomes & Value Statements
What We Can Achieve
| Outcome | iT-TRAC® | AISTA® |
|---|---|---|
| Risk Mitigation | iT-TRAC® identifiesIdentifies, manages and contains quality risks through structured exception handling, defect oversight, early validation and escalation visibility — reducing exposure and avoiding late-stage delivery failure. | AISTA® identifiesIdentifies and contains AI risk before deployment and after it, through structured assessment, defined permissions, behavioural monitoring and escalation — reducing exposure to failures that conventional testing does not detect. |
| Cost Optimisation | iT-TRAC® minimisesMinimises waste and reduces delivery cost by eliminating rework, reusing assets, targeting effort by risk profile, and ensuring test resources are proportionate to delivery value. | AISTA® directsDirects assurance effort by model criticality and exposure rather than uniformly, avoiding duplicated review across the three lines and concentrating scrutiny where the consequences are greatest. |
| Strategic Alignment | iT-TRAC® ensuresEnsures quality and test governance are explicitly aligned with delivery intent, stakeholder priorities and programme objectives — enabling accountable, value-focused assurance at every stage of change. | AISTA® ensuresEnsures AI adoption is governed against declared risk appetite and organisational objectives, so that what is permitted, and by whom, is decided deliberately rather than emerging from local initiative. |
| Competitive Advantage | iT-TRAC® strengthensStrengthens stakeholder trust and delivery credibility through early QA insight, visible assurance posture and audit-ready outputs — supporting confident decision-making during high-stakes delivery. | AISTA® establishesEstablishes demonstrable AI oversight ahead of regulatory obligation, allowing the organisation to adopt faster on the strength of evidence rather than pausing to construct governance under pressure. |
| Operational Excellence | iT-TRAC® enablesEnables scalable, efficient and repeatable quality practices through standardised test architecture, automation discipline and governance rhythm — reducing setup variance and increasing confidence in delivery quality. | AISTA® buildsBuilds a repeatable assurance practice for AI — inventory, classification, testing, monitoring and review — that scales with adoption instead of being rebuilt for every new use case. |
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Office
124 City Road, Suite G4005, London, EC1V 2NX
Hours
M-F: 09:00 - 17:00
S-S: Closed