Responsible AI can be overwhelming...

but it doesn't have to be.  


We help trustworthy businesses comply with secure AI regulations and maintain their brand through AI tests and audits.

Empower your business

Responsible AI and safe AI based on your business goals.  

Do it right

Get your org aligned on AI governance and compliance.

Smart results

Understand risks and how to fix them.

Sleep peacefully

Launch and monitor for privacy and safety. 

How we can help you

Compliance and Safety:

We provide the safety testing required by the EU AI Act, and can guide you on ISO compliance and the NIST AI framework.  


Continuous Audit or Red-Team:

Your organization is built on reputation and trust, and you want an external audit of your AI app. We combine a continuous audit and human red team test to monitor and measure your AI product.

AI Startups Roadmap:

For startup founders, we offer a DIY Roadmap to Responsible AI. This personalized strategic vision and coaching is a low-cost guide to best practices.  


Upgrade internal knowledge:

Build data protection culture and knowledge! We offer bespoke coaching: strategic decision-making for leaders, and game-based training for developers and technical staff. 

What Makes Us Different

Like having an in-house AI governance team and engineers

We bring the framework, development, and continuous audit for a successful AI product safety, from testing and audit to fixes. 

Safe foundations for your innovations

Validate the foundation so you can continue building safely. We use the NIST AI Risk Management framework and EU AI Safety Act guidelines.  


Products, not code projects

We ensure AI project ROI by providing metrics and continuous monitoring that will give you long-term confidence. It's not about the technology; it's about the best results for your company.  

Designed for you and your budget

We charge by the project, not by the hour, so you know what your budget will be.

Lead the Future. Do AI Right. 

Join the Responsible AI Movement!

Examples of Work 

Improve models by checking the training data:

By testing basic data hygiene in the machine learning build process, we were able to reduce threats to thousands of machine learning models in one tech company - effectively and efficiently.


Face recognition framework to protect privacy and prevent bias:

A democratic government agency wanted to protect civil liberties while automating border protection. We provided a framework for mitigant privacy risks and unfair bias in face recognition systems.

Location sharing for a mobility app:

We evaluated how to provide useful location information while still protecting their users' privacy using gold-standard methods.

This enabled them to partner with local metro authorities and grow their customer base! 

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