In today’s rapidly evolving AI environment, strong governance is more important than ever as organizations strive to harness the power of AI. With DataRobot’s 10 years of experience in enterprise AI, we’ve been committed to building an AI platform that: Ranked highest among 18 vendors recognized by Gartner in the Governance Use Case category.® We believe we have a governance framework that has proven to be superior in the marketplace and exceeds industry standards.
At DataRobot, we have always prioritized building a robust AI governance framework that enables our customers to confidently build, deploy, and monitor generative and predictive AI assets. This framework helps teams maintain the quality and integrity of assets in production, which is critical to ensuring sustainable value.
We believe these efforts have led to our highest ranking in Gartner’s Governance Use Case category.®We received an impressive governance score of 4.10 out of 5. In our opinion, this recognition demonstrates our unwavering commitment to maintaining the highest levels of integrity, quality, and transparency in all our AI operations.
Growing demand for robust AI and data governance
With the rise of generative AI, the need for trustworthy governance has never been stronger or more urgent. As AI becomes more deeply embedded in every sector, the potential risks associated with its deployment also increase.
In 2023 alone, the AI industry 40% increase in reported incidents The urgent need for a robust governance framework is highlighted by the data breach and model bias. A recent survey by PwC found that 85% of AI leaders cite governance as a top concern, highlighting the importance of trust, confidence, and the security of valuable intellectual property.
At DataRobot, our AI governance capabilities are specifically designed to address these critical requirements. Our platform provides comprehensive tools and protocols to bridge the trust gap for our customers.
DataRobot enables you to quickly and securely deploy machine learning and generative AI applications into production in average time. 2~4 weeks. This accelerated deployment is facilitated by features such as automated compliance documentation, real-time risk management, full model transparency, and most importantly, robust protection and intervention methods.
Our focus on governance and speed means our customers can stay ahead of the competition in AI without worrying about reputational damage or costly compliance issues.
Key governance features that differentiate DataRobot
AI has always been a team sport, and generative AI has made AI assets more accessible to a wider audience, increasing the need for collaboration. It is essential to meet high governance standards at every stage of the AI lifecycle: building, testing, production, and management.
DataRobot Governance Umbrella
The DataRobot Governance Umbrella outlines a comprehensive approach to governance standards for ML and GenAI development and management.
Our AI governance framework is designed to ensure AI solutions are effective, efficient, and compliant, ultimately ensuring value from AI. It also extends compliance capabilities by mitigating risk across all AI assets across the end-to-end AI process.
- Build Steps: Data scientists and AI practitioners lay the foundation for building powerful AI solutions.
- Testing phase: Models undergo rigorous testing to ensure they meet our standards and perform reliably under a variety of conditions.
- Production stage: Models are deployed and managed in a live environment.
- Monitoring and Management Steps: Oversight and governance tools help teams maintain compliance, integrity, and accuracy of AI solutions for operational excellence.
Our framework secures AI models and aligns them with operational and compliance goals. To do this, the DataRobot platform provides six unique capabilities that enhance each step of the framework and make DataRobot stand out.
- Visibility and Traceability: Full traceability of data, model lineage, and versioning allows you to track and document all changes, making your applications secure and usable.
- Audit and Compliance Documentation: Automatically generate compliance reports and audit trails to meet regulatory requirements and ensure transparency.
- Unique LLM Assessments and Tests: Detect potential risks and evaluate predictive and generative AI models and benchmark performance using both synthetic and real-world datasets.
- CI/CD Testing: Ability to rank RAG experiments by running prototype tests and evaluating ML or generative solutions via quality metrics.
- Real-time intervention, adjustments and notifications: Provides continuous monitoring with the ability to be notified and intervene immediately when issues arise, leveraging security models and metrics.
- AI Catalog: Easily register, track, and version all your AI assets—whether built on the DataRobot AI Platform or not—through a secure, central hub.
Security collaboration across teams
Because our customers want to move fast, we prioritize data privacy, security, and efficiency from build to management.
DataRobot’s Workbench provides a unified environment for developing AI use cases, with capabilities for automated artifact registration for code, prompts, experiments, and more. This helps accelerate the creation and iteration of useful AI models without sacrificing safety or limiting collaboration.
DataRobot’s registry enables AI practitioners to catalog, version, and manage all their AI assets, giving them greater control over their models. Encryption at rest and Bring Your Own Key (BYOK) capabilities ensure that your information is always protected, enhancing trust and reliability.
Flexibility and adaptability
The DataRobot AI platform is one of the most open platforms for AI. We give users ultimate control and choice over their generative AI initiatives. The platform supports custom models, third-party APIs, and open source LLMs to avoid vendor lock-in and technical debt, and protect sensitive data.
This flexibility and complete governance behind the corporate firewall ensures that customers can adapt their AI initiatives to meet evolving business needs with trusted security. Our platform also provides built-in GPU support to accelerate model training and processing, enabling data scientists to quickly process complex calculations.
DataRobot provides equal governance for predictive and generative AI, ensuring comprehensive oversight and control of all AI models. Our governance framework provides powerful tools and protocols, including full model transparency, real-time risk management, and automated compliance documentation. Whether deploying predictive models or generative AI applications, our platform ensures that all AI assets adhere to the highest standards of security, integrity, and accountability. This balanced approach allows customers to confidently and efficiently manage all their AI initiatives, knowing that predictive and generative models are governed with the same level of rigor and precision.
Gartner Recognition, Leader’s Trust
Our governance framework has been praised by industry analysts, highlighting the real value and reliability our platform delivers. In addition, DataRobot is ranked highest in Gartner’s governance use cases.
While this recognition from Gartner means a lot to us, the most impactful feedback comes from our customer community. Their testimonials highlight how our robust governance capabilities have positively impacted their AI initiatives, ensuring safe, successful, and confident deployments.
Tom Thomas, Vice President of Data Strategy, Analytics and Business Intelligence at FordDirect
“DataRobot is an indispensable partner in helping us maintain our reputation both internally and externally by responsibly and effectively deploying, monitoring, and managing generative AI.”
Arvind Thinagarajan, Vice President of Data Science and Analytics at Gannett | USA Today Network
“With DataRobot, we have already automated several steps in the machine learning lifecycle for hundreds of models, most of which are currently in the predictive AI space. This enables us to drive efficiency and save time for our data scientist teams through steps such as data preprocessing, model building, governance of those models, and performance measurement of those models. We believe our partnership can extend into the generative AI space.”
At DataRobot, we are committed to helping our customers achieve their goals with confidence and excellence. Our governance, recognized by Gartner and praised by our customers, underscores our commitment to providing a trustworthy, transparent, and accountable AI platform. We are proud to be the trusted choice for organizations looking to leverage AI responsibly and effectively.
Schedule a product tour and learn how our AI governance and compliance capabilities can help you quickly achieve value and effectively scale your AI use cases.
Gartner Critical CapabilitiesTM Data Science and Machine Learning Platforms, Machine Learning (ML) Engineering, Apraz Jafri, Aura Poppa, Peter Krensky, Jim Hare, Tong Jang, Maryam Hasanlu, Ragvendar Bhatti, published on June 24, 2024.
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Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from DataRobot.
About the author
Aslihan Buner is a Senior Product Marketing Manager at DataRobot, responsible for AI Observability, where she builds and executes go-to-market strategies for LLMOps and MLOps products. She works with product management and development teams to strategically identify and implement messaging and positioning while identifying key customer needs. Her passion is targeting market gaps, solving pain points across all verticals, and connecting them to solutions.
Meet Aslihan Buner
Katerina Bozhenko is an AI Production Product Manager at DataRobot, with extensive experience building AI solutions. With a degree in International Business and Healthcare Administration, she is passionate about helping users put their AI models to work effectively, maximizing ROI and experiencing the true magic of innovation.
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