We specialise in evidenced AI assurance
Minimising risk and maximising benefits
AI assurance ensures your AI…
Delivers as intended
AI assurance ensures your AI model or system does everything it is intended to do – and nothing that it shouldn’t.
It assesses design, development, outputs, governance structures and risk levels across multiple evaluation points – at the frequency and depth you require. It helps mitigate the risks of unintended consequences or failures that could impact operations, financial performance or stakeholder trust.
01
Reflects your values
AI systems should operate in line with your organisation’s values, legal duties and ethical standards.
Assurance identifies risks such as bias, unfairness, or opacity and provides the tools to prepare for compliance with regulatory frameworks, standards and codes of conduct. It supports accountability, reputation enhancement, and responsible innovation – unlocking strategic and financial benefits.
02
Fits the context
No AI system works in a vacuum.
Assurance helps assess whether a model is appropriate for the real-world context it’s being deployed in. It ensures that AI is not only technically accurate, but operationally safe, socially acceptable and proportionate to its use case.
03
[ Step 1 ]
Creating your AI roadmap requires input from diverse areas of your organisation
[ Step 2 ]
The challenge is to unite them to enhance your AI strategy
Two questions
you should
be asking
Who is responsible for developing and implementing AI solutions internally?
[Hint: It should involve more than engineers and tech teams]
How are you integrating AI assurance into your AI development strategy?
How our platform can help
Compliance
Our platform prepares for compliance with relevant legislation, such as the EU’s AI Act, GDPR, the US Executive Order on AI, and California’s AI Safety Bill, or the UK’s AI Standards Hub. It can help identify the right path for your needs.
It can also guide you through globally recognised AI standards, such as ISO/IEC 42001 for AI governance and NIST guidelines for trustworthy AI. Aligning your AI development with these standards mitigates risks and builds stakeholder trust.
Responsible assurance
It can assess the extent to which your AI model’s outputs are explainable and do not increase risks or harm to your organisation, its customers, and specific groups of people. It will evaluate and assess your existing responsible and ethical AI frameworks and related policies against best practice and AI standards related to bias, explainability, fairness, and accountability (amongst other evaluation dimensions).
Risk
The platform accesses risks beyond model risks and includes operational, customer, and reputational risks. The assurance process provides a critical assessment of your model’s or system’s design and performance to improve reliability, robustness, and security and can identify gaps in the training data that may obstruct reliable performance.
Reputational and operational risks related to unintended and malicious use cases can be identified and recommendations made for mitigation.
Values
Any AI developed or deployed should reflect the values of your organisation. The platform’s assurance process can help identify the core values that are reflected in your AI initiatives, how they represent your culture, sector or industry ethics and align with your long-term goals. Whether prioritising fairness, transparency, or sustainability, or developing ‘tools not creatures’, the assurance process can help you shape the values-based framework that will inform every stage of your AI development.
Enablement
As AI continues to transform industries it is essential to identify workforce AI gaps, as well as talent, ensuring your broader organisation is not only equipped with the technical skills needed to work with AI – but also with an understanding of the challenges and opportunities that come with it. The platform’s assurance process includes an option to incorporate people capability and enablement evaluations which can identify how capable and empowered your team feel to navigate the complexities of AI with confidence and integrity.