Model inventory
A register of AI systems, data sources and risk classifications you can maintain.
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AI & Information Services
Industry focus
Models are governed by their inputs. So is your liability.
Organizations building or deploying AI face questions about training data provenance, transparency, automated decisions and vendor accountability — often before regulation settles.
We build defensible AI governance now: documented data sourcing, risk assessment, human oversight and contractual allocation of responsibility.
How we add value
AI risk is a data and documentation problem before it is a legal one.
We assess how models are trained, evaluated and monitored, then document the decisions that regulators, customers and courts will later ask about.
We negotiate AI-specific terms with vendors and customers: usage rights, output ownership, confidentiality of inputs and limits on further training.
Impact assessment
Structured assessments for automated decision-making and high-risk use cases.
AI contracting
Usage, output, confidentiality and no-further-training terms with vendors and clients.
Oversight design
Human review, escalation and logging practices that make accountability real.
- AI Governance
- Training Data
- Automated Decisions
- Transparency
- Vendor Terms
Who It’s For
- AI product companies and data providers
- Enterprises deploying AI in regulated workflows
- Teams facing customer or regulator questions about AI use
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Related areas of expertise
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The experts leading our AI & Information Services practice
Recognized professionals who have guided organizations through these issues and bring that experience to your file.
