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AI Anywhere | Domino Nexus

Go Above
& Beyond

Unlock the Full Potential of AI – Fast, Responsibly, Economically

As enterprises begin to embrace Large Language Models (LLMs) and seek enterprise-wide AI business transformation, data science executives are realizing that hiring top talent simply isn’t enough to create a broad and bottom-line impact without an AI platform. Deliver more models, boost productivity, and lower infrastructure costs with Domino’s unified platform powered by NVIDIA:

– Deliver Value Now: Turn data science into a profit center by delivering 2x more production models.
– Boost Data Scientist Productivity & Elinate IT Lift: Automate devops through self-serve data scientist tooling while consolidating disparate stacks.
– Reduce Infrastructure Sprawl and Costs: Shrink infrastructure and cloud costs by up to 40%.

AI Anywhere | Domino Nexus

Go Above
& Beyond

Unlock the Full Potential of AI – Fast, Responsibly, Economically

Leading enterprises are using data science and artificial intelligence to create a competitive advantage. This includes generative AI, computer vision, and other advanced machine learning techniques. 

Responsible AI at enterprise scale means focusing on people, process, and overall governance of data and analytics practices. Enterprises must transition data science to a consistent, unified platform—powered by the latest in accelerated computing infrastructure —to bring together people and technology.

AI Anywhere | Domino Nexus

Go Above
& Beyond

Scale Advanced Analytics Across Hybrid-Cloud & Multi-Cloud

Leading enterprises are using data science and artificial intelligence to create a competitive advantage. This includes generative AI, computer vision, and other advanced machine learning techniques. 

Responsible AI at enterprise scale means focusing on people, process, and overall governance of data and analytics practices. Enterprises must transition data science to a consistent, unified platform—powered by the latest in accelerated computing infrastructure —to bring together people and technology.

Building an Industry Competitive Advantage

Percentage of organizations rating AI/ML important/very important:

Learn More: Ventana Research | Top 5 Considerations for Data and Analytics Executives

Technology Organizations

Technology Organizations

Technology organizations use AI to automate repetitive tasks, personalize the customer experience, enhance product development, and improve data analysis.

Financial Services

Financial Services

Financial organizations can predict and assess loan risks, improve loan underwriting, reduce financial risk, and detect crime thanks to
AI and ML.

Healthcare & Life Sciences

Healthcare & Life Sciences

Healthcare organizations transform drug development and diagnostics while reducing costs and increasing healthcare accessibility with the help of AI and ML.

Building an Industry Competitive Advantage

Percentage of organizations rating AI/ML important/very important:

Leanr More: Ventana Research | Top 5 Considerations for Data and Analytics Executives 

Technology Organizations

Technology Organizations

Technology organizations use AI to automate repetitive tasks, personalize the customer experience, enhance product development, and improve data analysis.

Financial Services

Financial Services

Financial organizations can predict and assess loan risks, improve loan underwriting, reduce financial risk, and detect crime thanks to
AI and ML.

Healthcare & Life Sciences

Healthcare & Life Sciences

Healthcare organizations transform drug development and diagnostics while reducing costs and increasing healthcare accessibility with the help of AI and ML.

Operationalizing AI at Scale is Challenging

“Less than one in 10 organizations consider their organization’s AI/ML technology completely adequate. Two-thirds of organizations consider it less than adequate.”
Learn More: Ventana Research | Top 5 Considerations for Data and Analytics Executives

AI Workloads Have Demanding (and Costly) Requirements.

AI/ML model development requires scalable infrastructure and flexible tooling.

Learn More: Operationalize AI at Scale: Closing the Divide Between Data Science and IT

Purpose-Built Infrastructure is Required

Purpose-Built Infrastructure is Required

Compute-intensive model training and development calls for specialized infrastructure, such as GPUs.

Workloads are Intensive & Variable

Workloads are Intensive & Variable

Peak utilization during model training is much greater than average utilization, requiring scalable, elastic resources.

AI Requires Flexibility

AI Requires Flexibility

Data scientists developing AI models work with a variety of open-source tools, languages (Python, R, SAS, etc.), and packages.

AI Workloads Have Demanding (and Costly) Requirements.

AI/ML model development requires scalable infrastructure and flexible tooling.

Learn More: Operationalize AI at Scale: Closing the Divide Between Data Science and IT

Purpose-Built Infrastructure is Required

Purpose-Built Infrastructure is Required

Compute-intensive model training and development calls for specialized infrastructure such as GPUs.

Workloads are Intensive & Variable

Workloads are Intensive & Variable

Peak utilization during model training is much greater than average utilization, requiring scalable, elastic resources.

AI Requires Flexibility

AI Requires Flexibility

Data scientists developing AI models work with a variety of open-source tools, languages (Python, R, SAS, etc.), and packages.

Embracing Hybrid-Cloud &
Multi-Cloud MLOps to Meet AI Demands

Advanced enterprises are repatriating AI workloads back on-prem — while simultaneously exploiting the flexibility of multiple clouds — for performance and cost optimization.

Many organizations lack a hybrid strategy and are “stuck with hybrid” due to piecemeal modernization efforts, regulations, acquisitions, and shadow IT.

Learn More
92% of enterprises have a multi-cloud strategy
87% of enterprises have a hybrid strategy

Cloud & Technology Sprawl Hinder AI Success

A lack of a holistic, hybrid MLOPs strategy results in an unorganized, uncontrolled sprawl of infrastructure and services — limiting agility and innovation.

Distributed, Inflexible Infrastructure & Tooling Creates Silos

Governance, Regulation, & Security Concerns Slow Innovation

Inflexible, Proprietary Technology & Vendor Lock-in Increases Costs

Inflexible, Proprietary Technology and Vendor Lock-in Increases Costs
Cost Mitigation

By 2024, 75% of the global population will have personal data covered under privacy regulations. More than 100 countries already have data sovereignty regulations – often specifying where data must be collected, processed, and stored.

This creates complexity for global data science and IT teams aiming to share AI best practices across geographies while standardizing security and governance.

Governance, Regulation, and Security Concerns Hinder Innovation
Data Sovereignty

By 2024, 75% of the global population will have personal data covered under privacy regulations. More than 100 countries already have data sovereignty regulations – often specifying where data must be collected, processed, and stored.

This creates complexity for global data science and IT teams aiming to share AI best practices across geographies while standardizing security and governance.

Distributed, Inflexible Infrastructure & Tooling Creates Silos
Knowledge Silos

More than half of organizations deploy analytics and data technologies using a hybrid of on-premises and cloud platforms – and data gravity attracts applications and services.

By 2025, more than 75% of enterprises will have data management products spanning multiple cloud providers and on-premises data centers. Disparate silos across data, infrastructure, tools, and teams – limit data science team productivity and slow AI innovation.

Learn More: Ventana Research | Top 5 Considerations for Data and Analytics Executives
More than half of organizations deploy analytics and data technologies using a hybrid of on-premises and cloud platforms - and data gravity attracts applications and services.

By 2025, more than 75% of enterprises will have data management products spanning multiple cloud providers and on-premises data centers. Disparate silos across data, infrastructure, tools, and teams - limit data science team productivity and slow AI innovation.

Source: Top 5 Whitepaper, Ventana Research

Knowledge Silos

Distributed, Inflexible Infrastructure & Tooling Creates Silos

By 2024, 75% of the global population will have personal data covered under privacy regulations. More than 100 countries already have data sovereignty regulations – often specifying where data must be collected, processed, and stored.

This creates complexity for global data science and IT teams aiming to share AI best practices across geographies while standardizing security and governance.

Source: Top 5 Whitepaper, Ventana Research

Data Sovereignty

Governance, Regulation, and Security Concerns Hinder Innovation

By 2024, 75% of the global population will have personal data covered under privacy regulations. More than 100 countries already have data sovereignty regulations – often specifying where data must be collected, processed, and stored.

This creates complexity for global data science and IT teams aiming to share AI best practices across geographies while standardizing security and governance.

Source: Top 5 Whitepaper, Ventana Research

Cost Mitigation

Inflexible, Proprietary Technology and Vendor Lock-in Increases Costs

Domino Nexus

Unleash Hybrid & Multi-Cloud Data Science

Unleash Hybrid & Multi-Cloud Data Science

Domino Nexus lets you run data science and machine learning workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, so you have one place to build, deploy, and monitor models.

FOR DATA SCIENCE LEADERS

Increase innovation and productivity through worldwide collaboration and shared best practices.

FOR IT TEAMS

Centrally govern all data science activity while maintaining consistent operations for standardized governance, cost-mitigation, and preventing vendor lock-in.

FOR DATA SCIENTISTS

Deploy models faster by building off of prior work with self-serve access to tools and infrastructure.

Capture Real Benefits

Take advantage of the revolutionary capabilities of the Domino Nexus platform to
optimize your technology and further your business objectives.

Protect

Protect Data Sovereignty

Ensure customer trust and regulatory compliance and protect data sovereignty with consistent processes, centralized and controlled data access, and limited access to sensitive data.
Optimize

Optimize Cost and Performance

Run data science workloads where they make the most sense based on cost, performance, and regulatory considerations by leveraging the benefits of both on-premises and cloud technology.
Standardize

Standardize Across Clouds

Break down silos and manage risks by reducing technology sprawl and standardizing security and governance best practices across the hybrid- and multi-cloud.
Share

Share Code Without Sharing the Data

Increase productivity by compounding knowledge worldwide - share models and code from a single repository without sharing sensitive data.
Operationalize

Operationalize AI at Scale

Increase the volume and quality of data science models in production that inform new offerings, improve customer experiences, and increase profitability.
Modernize

Modernize to Recruit Top Talent

Recruit top data science talent and give them the cutting-edge tools they need to do their best work.

Elements for AI Success

Engage Top Data Science Talent

Engage Top Data Science Talent

Hire and retain top talent with a platform enabling worldwide collaboration, self-serve access to modern tools, and seamless end-to-end model lifecycle management.

Centralize & Govern Data Science

Centralize & Govern Data Science

Keep customer trust, ensure regulatory compliance, and maximize productivity by breaking down technology and infrastructure silos.

Build a Data Culture

Build a Data Culture

Scale data science as a core competency so you can increase the volume and quality of data science models to inform key decisions – Upskill data and analytics expertise on a common platform.

Elements for AI Success

Engage Top Data Science Talent

Engage Top Data Science Talent

Hire and retain top talent with a platform enabling worldwide collaboration, self-serve access to modern tools, and seamless end-to-end model lifecycle management.

Centralize & Govern Data Science

Centralize & Govern Data Science

Keep customer trust, ensure regulatory compliance, and maximize productivity by breaking down technology and infrastructure silos.

Build a Data Culture

Build a Data Culture

Scale data science as a core competency so you can increase the volume and quality of data science models to inform key decisions – Upskill data and analytics expertise on a common platform.

AI Anywhere | Go Above and Beyond

Companies are gaining a competitive advantage using the benefits of hybrid-cloud and multi-cloud AI strategies for cost and performance optimization.

Productivity

Svg Vector Icons : http://www.onlinewebfonts.com/icon 21% increase in model accuracy
A hybrid workload placement strategy at Johnson & Johnson focuses data scientists on model tuning rather than DevOps. Discover How
Svg Vector Icons : http://www.onlinewebfonts.com/icon 10x more productive
Self-serve hybrid- and multi-cloud infrastructure and tooling scales across thousands of users at Lockheed Martin Discover How
Svg Vector Icons : http://www.onlinewebfonts.com/icon Company-wide impact

Allstate guides thousands of decision-making actions with models, helping 17,000 adjusters resolve claims faster.
Discover How

Governance

Svg Vector Icons : http://www.onlinewebfonts.com/icon 20%+ efficiency gain with flat costs

A hybrid workload placement strategy at Johnson & Johnson sustains a 20% growth in compute and 30% growth in storage with near flat costs.

Learn More

Svg Vector Icons : http://www.onlinewebfonts.com/icon $20m+ in annual cost savings

Automation, centralization, and reproducibility creates efficiencies at Lockheed Martin.
Learn How

Svg Vector Icons : http://www.onlinewebfonts.com/icon 542% three-year ROI

Domino customers experience $30 milllion in total economic impact over three years, as confirmed by our Forrester® Total Economic Impact™ report.
Learn More

Impact

Svg Vector Icons : http://www.onlinewebfonts.com/icon 10x more projects

Standardization of data, models, and applications in Domino’s unified platform helped Johnson & Johnson scale data science impact.
Discover How

Svg Vector Icons : http://www.onlinewebfonts.com/icon 10x - 100x efficiency gains
More efficient data scientists at Lockheed Martin drive innovation and new revenue streams. Learn How
Svg Vector Icons : http://www.onlinewebfonts.com/icon New Fraud Detection in weeks, not months

Topdanmark automates 65%+ of cases for processing coverage and claims.
Learn How

Now It’s Your Turn

Discover how to run data science and machine learning workloads across any compute cluster with Domino and NVIDIA with three simple steps: 

Unify data science across silos using Domino’s Enterprise MLOps Platform powered by NVIDIA AI solutions.

Step 01

Build a modern data science platform to attract, retain, and upskill top talent.

Step 02

Reap the benefits of a competitive advantage with more models deployed in production applications.

Step 03

Now It’s Your Turn

Discover how to run data science and machine learning workloads across any compute cluster with Domino and NVIDIA with three simple steps: 

step 01

Unify data science across silos using Domino’s Enterprise MLOps Platform powered by NVIDIA AI solutions.

step 02

Build a modern data science platform to attract, retain, and upskill top talent.

step 03

Reap the benefits of a competitive advantage with more models deployed in production applications.

Domino Data Lab, in partnership with NVIDIA, supports open, collaborative, reproducible model development, training, deployment, and management free of DevOps constraints—all powered by efficient, end-to-end compute. Democratize GPU access by enabling data science teams with powerful NVIDIA AI solutions paired with Domino’s leading Enterprise MLOps platform. You can do it all on premises, in the cloud, or in the modern hybrid cloud with Domino Nexus.

Learn more about Domino Nexus
Try Domino on NVIDIA LaunchPad