Domino Data Lab Transforms AI Governance from Innovation Tax into Value Driver

Domino Governance is the first solution for model builders and auditors to mitigate risk within model development processes, shortening the governed AI lifecycle by up to 70%

SAN FRANCISCO, Oct. 8, 2024 /PRNewswire/ -- Domino Data Lab, provider of the leading Enterprise AI Platform trusted by the largest AI-driven companies, today announced Domino Governance, a new solution for mitigating AI's risks while accelerating its rewards. Its unique approach automatically orchestrates the fully governed model lifecycle. Domino Governance is the first solution to embed AI governance within the data science workflow — putting policies, evidence and approvals in one place and on schedule for enterprises to quickly and safely innovate.

Enterprises today are at the nexus of powerful forces. As new AI technologies, use cases, and regulations emerge, responsible AI is now a top-three priority for AI leaders. Meanwhile, the Organization for Economic Co-operation and Development estimates global AI incidents have risen more than 2000% since 2022. Therefore, it is no surprise that 95% of enterprises say they need a new AI governance approach in order to avoid penalties, lost reputation or revenue as AI initiatives mount.

"AI governance transcends compliance—it's a critical value driver in today's model-driven landscape," said John K. Thompson, author of Building Analytics Teams and a leader of highly successful enterprise data science teams. "By moving from high-level principles to actionable best practices, organizations can mitigate inherent risks in AI without slowing innovation, unlocking immense value across mission-critical sectors like finance and biopharmaceuticals."

Current AI governance, a bolt-on practice of manually assessing and mitigating AI risks, stalls AI initiatives, turning momentum into complexity. It introduces post-development delays, wastes resources and leaves residual risk: models can take twice as long to validate than build, and bespoke approaches to compliance with any regulation can take months, meanwhile leaving enterprises exposed. Domino Governance's unique approach automates and orchestrates the collection, review, and tracing of materials required to ensure compliance with internal and external policies throughout the entire AI and ML development process.

"Companies shouldn't have to sacrifice speed of innovation for the sake of compliance," said Nick Elprin, co-founder and CEO at Domino. "Whether our customers are building models that help bring new life-saving therapies to market, keep our financial system safe, or help defend our country, we are proud to help them innovate rapidly while staying safe and responsible."

Transforming governance into a swift and dependable process
Domino Governance makes every policy actionable and enforceable across model builders and auditors. Unlike with bolt-on, standalone solutions, policies are defined and enforced where models are built and operated, shortening time-to-value and improving risk mitigation. This automated approach eliminates months of post-development model validation time, which can reduce the governed model lifecycle by an estimated 70%. Unlike black-box compliance solutions requiring mandatory professional services, Domino gives enterprises full control of policies, which shortens the time to comply with new policies from months to weeks, and allows teams to adopt new technologies at any time.

"Streamlined governance creates a tremendous advantage for enterprises navigating complex regulatory environments and their own unique governance journey," said Shawn Rogers, CEO at BARC US. "Domino's approach to AI governance makes compliance seamless and less error-prone, helping organizations avoid pitfalls while fostering innovation."

Domino Governance delivers both AI development and compliance teams:

• Fully configurable policy management. Policies can be easily defined from scratch or customized from off-the-shelf templates based on frameworks such as the EU AI Act and the National Institute of Standards and Technology's AI Risk Management Framework. Only Domino Governance allows customers to create and edit policies without any required professional services. It also accelerates compliance by giving reviewers instant capabilities to audit data, see work context, and review packaged evidence — all without disrupting production.
• Collaborative and automated evidence collection. Once set, policies are automatically enforced at the same time and in the same place where models are built and operated, increasing speed and consistency. The platform autonomously captures evidence of enforcement by asking questions of the right people at the right time and seeks approvals using stakeholders' AI tools spanning the full spectrum of AI, from data science to generative AI.
• Global compliance visibility. Domino provides one place to see policies, status of compliance, and open actions across all projects and models developed and deployed anywhere. It offers complete visibility into and across AI project risks via one cross-platform dashboard. Domino also provides an API-led integration to connect to other risk-related platforms, such as governance, risk and compliance systems.

Powering Compliance and Innovation Across Highly Regulated Industries
With proper governance, enterprises can comply with regulations and responsible AI principles, and transform mission-critical use cases such as Model Risk Management in Financial Services and Statistical Computing Environment (SCE) Quality Control (QC) in Life Sciences. Governance deeply impacts the value of AI by mitigating risks, reducing costs, and accelerating innovation. Domino complements these capabilities with a governance maturity assessment and services offering for enterprises to establish, and deliver on their AI governance strategy.

Banking on Built-in Governance and Openness 
Domino Governance builds on the company's heritage of enabling highly governable AI innovation at scale for enterprises in the most regulated markets. Domino's existing governance foundation has set industry standards with capabilities for best-in-class reproducibility —enabling audit documentation by automatically recording all model, data, code, environments and versions— and integrated Model Monitoring to detect and address drift and performance issues across all types of AI and data built and deployed across any hybrid, multi-cloud or on-premises environment.

Domino's governance foundation complements its open, pluggable architecture which enables customers and partners to bring their preferred tools, data, and infrastructure — on-premises or in any cloud — to a unified platform. Additionally, much of Domino's functionality is available programmatically through public API endpoints. With Domino Governance, the company takes this foundation further by building on its reproducibility engine in a way that helps enterprises proactively mitigate risks across all AI while accelerating time to market.

Availability
Domino Governance will be generally available this month.

Additional Resources

• Learn more about Domino Governance.
• Attend a webinar, Mitigating AI risks: A governance strategy for new threats, technologies, and new regulations, featuring experts from AWS, Dresner Advisory Services and Domino on Oct. 22.
• Learn more about the latest innovations in the Domino Enterprise AI Platform.
• Read our blog to discover how Domino can help make AI responsible and compliant by default.
• Follow Domino on LinkedIn and X.

About Domino Data Lab
Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino's Enterprise AI Platform provides an integrated experience encompassing model development, MLOps, collaboration, and governance. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors. Learn more at www.domino.ai.

SOURCE Domino Data Lab