Artificial Intelligence
Artificial Intelligence
We work both sides of AI: building solutions for clients across use cases, and governing AI systems so they meet emerging regulatory expectations. Most firms in this space do one or the other — advise on governance without ever having built a model, or build systems without real regulatory fluency. We do both, which means our governance advice is grounded in how these systems actually get built, and our development work is grounded in how they'll actually be regulated.
AI regulation is moving fast and unevenly across jurisdictions — the EU AI Act, NIST AI RMF, and a growing set of sector- and state-specific rules don't yet form one coherent framework. We help organizations build AI governance that's durable across that shifting landscape, not compliance built to satisfy whichever rule is loudest this quarter.
01
AI Solution Development
We design and build AI solutions for clients across use cases — from targeted automation to more ambitious applications — with governance and compliance considerations built in from the first design decision, not bolted on before launch.
02
AI Governance Framework Design
Governance frameworks that define how AI systems get approved, monitored, and retired within your organization — ownership, risk tiers, and review gates that scale as you adopt more AI, rather than ad hoc case-by-case decisions.
03
AI Impact Assessments (NIST AI RMF-aligned)
Structured impact assessments for AI systems, aligned to the NIST AI Risk Management Framework, evaluating risk to individuals and the organization before deployment — the AI-specific counterpart to a DPIA.
04
AI Regulatory Compliance (EU AI Act, NIST AI RMF, cross-market)
Compliance advisory across the AI-specific regulatory landscape — EU AI Act risk-tiering and obligations, NIST AI RMF alignment, and the emerging rules in other markets — reconciled into one compliance posture for organizations deploying AI globally.
05
Responsible / Ethical AI Advisory
Advisory on the responsible-AI questions that sit alongside strict legal compliance — transparency to users, appropriate human oversight, and use-case decisions that hold up to scrutiny beyond the letter of any single regulation.
06
Privacy-by-Design for AI/ML Development
Privacy embedded directly into AI/ML development — training data provenance, data minimization in model design, and privacy-preserving techniques — so AI systems don't become the weakest link in an otherwise sound privacy program.
07
Automated Compliance Workflow Development
We build automated workflows that operationalize compliance obligations — DSAR routing, consent enforcement, policy checks embedded in deployment pipelines — turning manual compliance processes into systems that run reliably at scale.
08
Algorithmic Bias & Fairness Assessments
Assessment of AI systems for bias and disparate impact across relevant populations, with concrete remediation guidance — a technical and regulatory risk that's increasingly a specific, named obligation rather than a general good-practice suggestion.
09
AI Vendor / Third-Party Tool Risk Assessments
Risk assessment of third-party AI tools and vendors before adoption — how they handle your data, what they claim about model behavior, and whether their compliance posture holds up — since most organizations' AI risk today comes from tools they didn't build.
10
Cross-Market AI Compliance (US/EU/UK/APAC)
AI compliance advisory for organizations deploying the same systems across the US, EU, UK, and APAC markets simultaneously, reconciling divergent AI-specific rules into a single deployment strategy instead of a market-by-market scramble.