Rapid Acceleration of AI Adoption Amplifies Risk
AI brings changes and risks for organizations - security, rules, and compliance. Protecting AI systems and meeting regulations is a top priority for security, data science, and compliance teams, as well as executives.
Broken Data Pipelines
Unexpected Model Behavior
A powerful holistic view of all AI governance activities with real-time alerts and complete visibility of project progress. Understand your organization's aggregate AI governance position at a glance.
Start risk management by cataloging AI models using our API. Assign owners and access audits easily.
Generate internal reports and share your compliance publicly in your AI trust center.
Auto Generate Reports
Generate different reports for different stakeholders, so everyone is kept in the loop.
Vendor Risk Management
In development now. Request early access to be the first with access to vendor risk management.
Comprehensive policy Frameworks
Best-in-class policy frameworks, designed by industry experts, ready to use from day one.
Ready to use
Europe’s AI Act
The UK’s pro-innovation approach to regulating AI
Canada’s AI and Data Act
Industry specific frameworks, such as SR 11-7 and the PRA’s guidance on model risk
Add your own…
PureML is AI Risk management platform for everyone
Compliance, Risk, Legal, and Privacy Officers
- Address regulatory demands for transparent reporting and disclosures
- Establish a consistent framework for assessing and managing Responsible AI (RAI) practices organization-wide
- Ensure compliance with internal and external mandates for large-scale AI applications, with guaranteed auditability of governance materials
AI Leaders & Data Science Teams
- Take preemptive measures to minimize risks stemming from AI and ML systems falling short of governance standards.
- Enhance the automation within the AI/ML development process to streamline governance procedures.
- Effortlessly produce governance documents without incurring additional administrative burdens.
Business Leaders & AI Product Owners
- Improve AI ROI through strong governance and risk mitigation.
- Address customer expectations for AI transparency in sales interactions.
- Protect generative AI projects from regulatory changes and risks, such as IP leakage and mishandling of personally identifiable information (PII).