Domino powers model-driven business for the world’s most advanced enterprises, including over 20% of the Fortune 100. Our Enterprise MLOps platform speeds up the development and deployment of data science work while increasing collaboration and governance, to scale data science into a competitive advantage.

Our platform enables thousands of data scientists to develop better medicines, grow more productive crops, adapt risk models to major economic shifts, build better cars, improve customer support, or simply recommend the best purchase to make at the right time. 

In regulated industries like life sciences, accelerating research while ensuring compliance is crucial. With LLMs and Retrieval Augmented Generation (RAG), researchers can ask real-time questions about clinical trial documents, extracting insights that drive faster, data-backed decisions.

Join Domino as we demonstrate how to use LLMs and RAG for clinical trial summarization – unifying data, compute, and AI tool management to optimize performance, cut costs, and accelerate AI from experimentation to production.

In this webinar, we’ll show how to use Domino to:

- Deploy LLMs to Amazon SageMaker for scalable, governed inference.
- Use AWS Trainium and Inferentia for accelerated training and inference.
- Access large language models via Amazon Bedrock, backed by Domino’s governance capabilities.
- Centralize model development and monitoring through Domino’s unified platform.

Faster answers, better decisions: ML-powered document analysis

Watch this session to understand how AI is transforming government and what agencies must do to stay ahead in an era of rapid technological change. Our expert panel will discuss:

- AI policies and mandates: Impact of shifting priorities on federal AI adoption.
- Geopolitical competition: Global AI’s influence on defense strategies.
- Federal and military AI adoption: Progress in leveraging AI to maintain a strategic edge.
- Advancements in government AI: Overcoming barriers to operationalize AI for mission-critical use cases.
- AI governance: The rise of responsible AI practices.

AI in public sector: Predictions for AI in federal policy, national security, and geopolitics

The transformational power of AI is undeniable, but many enterprises struggle to scale amidst infrastructure complexity, regulatory pressures, and talent shortages. Organizations must navigate fragmented environments, rising cloud costs, and the need for robust governance.

In this session, Domino Data Lab and NetApp explore key challenges in AI adoption, including unifying data and model pipeline management and compliance.

We’ll also discuss::
- Overcoming infrastructure fragmentation to enable seamless AI scaling.
- Addressing governance and compliance in highly regulated industries.
- Bridging the gap between data science and IT to drive operational efficiency.
- Predictions on unifying data, AI, and infrastructure to drive agility and long-term growth.

AI in perspective: What’s next in enterprise AI?

Explore how AI is revolutionizing life sciences by driving advancements in drug discovery, diagnostics, and compliance. Join us to uncover the transformative potential of AI and its impact on innovation in healthcare.

- AI-driven drug discovery: Moving from proof-of-concept to practical applications.
- Enhanced diagnostics: AI improving speed and accuracy in imaging.
- LLMs in documentation: Revolutionizing clinical trial records and filings.
- Streamlined trials: Faster patient recruitment with AI-powered platforms.
- Compliance platforms: Real-time regulatory monitoring for life sciences.

Ai in life sciences: Transforming discovery, diagnosis, and innovation

AI technology advancements have outpaced the capabilities of legacy model risk management (MRM) systems, leaving critical vulnerabilities that can jeopardize compliance and result in financial losses and reputational harm. As financial institutions, banks, and insurance companies rely more on sophisticated AI/ML models to make decisions, modern MRM technology has become critical to managing the lifecycle of models —ensuring a swift and dependable process — without stalling innovation.

Watch this webinar and you’ll uncover:

- The limitations of traditional MRM systems and why they fall short in managing the complexities of modern AI/ML models.
- How advanced MRM technologies can seamlessly integrate into your institution's framework, mitigating unseen risks and protecting your organization.
- Strategies for aligning AI/ML models with your institution’s risk appetite, preventing compliance issues, and financial setbacks.
- Ways to balance successful risk mitigation and AI/ML innovation, while maintaining your institution's competitive edge.

Balancing Innovation and Risk: Navigating AI/ML Challenges with MRM

As AI in all its forms, from analytics to machine learning and Generative AI, is increasingly ready for mission-critical use cases, there’s a lot on the line. The potential to transform your organization and find new ways to accomplish your mission with AI is proven, but agencies still face hurdles to scaling AI.

During this session, we discuss:

Perspective from the U.S. Navy's Chief Digital and AI Officer on adopting AI to achieve mission critical outcomes.
- What agencies should know about AI risks.
- The toolsets and processes organizations need to sustainably create value from AI while mitigating risks.
- Actionable next steps to integrate AI rapidly, safely, and cost effectively.

Transformational AI adoption in the U.S. Navy

This discussion underscores the transformative potential of AI in government, emphasizing strategic implementation, scalable platforms, and governance as critical enablers.

Key Insights:
- Scalable AI tools help agencies like DOE streamline operations across offices.
- Systematic platforms ensure compliance, auditability, and user trust.
- Early successes (“quick wins”) are crucial for long-term adoption.

Scalable AI for a connected future: from policy to production

As AI adoption accelerates, your organization must be ready with future-proof and effective governance frameworks that drive innovation and risk mitigation across industries. This on-demand webinar is designed to offer risk, compliance, IT, data science, and analytics teams insightful strategies on navigating governance complexities — enabling you to transform them into a swift and dependable process.

You’ll hear real-world governance approaches from guests and thought leaders such as Forrester, the Federal Reserve Bank of New York (FRBNY), and Domino Data Lab — and discover how to:

- Craft and implement governance policies that meet multi-jurisdictional and organizational requirements, including unique considerations for Generative AI (GenAI).
- Assign accountability within AI governance structures, ensuring seamless operations and clear oversight.
- Uncover key metrics to evaluate the effectiveness of your AI governance framework, optimize business value, and enhance AI project visibility.

Master AI governance: Align innovation with risk mitigation

Our expert panelists at Domino and UCB will explore the key challenges driving SCE transformation for life sciences organizations, dive into the latest technological innovations, and help you understand governance's critical role in ensuring compliance, while optimizing workflows. Learn how to navigate this rapidly changing SCE landscape and leverage global collaboration to drive the next wave of innovation.

Watch this on-demand webinar and you’ll discover:

1. Key challenges of legacy SCE technology and the evolution of SCE
2. What’s new with today’s SCE technology – ways to enhance efficiency and collaboration
3. Why strong governance is critical in maintaining regulatory compliance and streamlining workflows
4. How to build a global network of collaboration, fueling innovation and progress
5. Top practices and future-proof SCE strategies to advance and drive clinical studies forward

Shaping the future of SCEs: The evolution of statistical computing environments

In today's fast-paced AI and ML landscape, managing risks is crucial for maintaining ethical, safe, and responsible systems. The National Institute of Standards and Technology's (NIST) AI Risk Management Framework (RMF), released in 2023, offers government agencies a comprehensive set of guidelines for effective AI governance. This webinar provides a concise overview of how to implement the NIST RMF at scale, to ensure your AI initiatives are secure, compliant, and aligned with mission-driven goals.

Watch this on-demand webinar and discover how to:
- Operationalize the NIST AI RMF to tackle governance challenges effectively.
- Apply the NIST framework’s core functions to align AI initiatives with organizational values and compliance requirements.
- Adopt the NIST AI RMF and enhance model transparency — and set the stage for ongoing regulatory compliance.

This webinar is ideal for AI/ML leaders, data scientists, risk officers, compliance managers, IT platform owners, and policymakers ensuring AI systems meet ethical and regulatory standards.

- AI/ML leaders and data scientists in government agencies
- Risk officers and compliance managers
- IT platform owners and decision-makers involved in AI initiatives
- Policymakers focused on AI governance and ethical considerations

Fast-track compliance with NIST AI RMF

In this webinar, hosted by AI and data science experts from Domino Data Lab, Dr. Kjell Carlsson, and Adam Gale, Business Cloud Architect for AI & Financial Industry at NetApp, we’ll guide you through the opportunities and challenges of implementing AI at scale in regulated environments, while ensuring compliance with the EU AI Act’s framework. This session will offer the critical insights you need to address the EU AI Act’s compliance requirements to ensure ethical, trustworthy AI that drives innovation.

Transforming governance complexities: Tackling the EU AI Act

In today's rapidly evolving AI landscape, emerging regulations and advancements in GenAI are intensifying the need for robust AI governance to reduce risks, accelerate innovation, and deliver on the full potential of AI. This webinar delves into the challenges data scientists and IT leaders face in making AI responsible, the emerging governance best practices and trends to watch, and the key drivers for establishing AI governance frameworks that evolve with the enterprise.

Join our webinar featuring industry experts and discover:

- What AI governance is and why it matters
- Trends and best practices on shaping the future of AI governance
- How to navigate the complexities of the AI landscape
- How to embed and enforce responsible AI policies
- Ways to reduce risks and accelerate innovation with a scalable governance framework
- Insights on creating an effective AI governance strategy – enabling risk mitigation, complying with regulations, and ensuring performance

Mitigating AI risks: A governance strategy for new threats, technologies, and new regulations

The hidden future of AI

Discover how AI is transforming the financial services and insurance industries, enabling smarter decision-making and value creation. Join us as we explore key advancements and challenges shaping the future of FSI.

- Unstructured data: LLMs extracting value for risk and operations.
- Agentic AI compliance: Managing stricter regulatory requirements.
- Model governance: Scaling oversight as AI democratizes model creation.
- Risk optimization: AI for credit analysis and fraud detection.
- AI governance: Transforming processes to manage compliance bottlenecks.

Unlocking unstructured data, agentic AI compliance, and managing risk

Financial Services

Insurance

Artificial Intelligence

Compliance

Regulations

Governance

Risk Management

Data Science

Unstructured Data

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Data and Analytics

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Unlocking unstructured data, agentic AI compliance, and managing risk

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