Modernize Your Business Faster with AI

Scale AI across the business

Streamline workflows and AI solution delivery 15x faster without tech stack disruptions

Generate meaningful results and value

Increase AI investment ROI without sacrificing quality

Manage all your AI initiatives in one place

Modzy for Executives

Accelerate your AI modernization

The business case for delivering real value from AI begins with Modzy.

1

Improve AI usability

Streamline ML workflows, improve employee experience, and delivery AI solutions faster

2

Reduce AI risk

Govern AI models centrally and confidently, with controls to monitor model performance

3

Save money

Discover and reuse AI models and cut cloud costs with reduced compute for inference

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Overview of MLOps Architectures

Learn about the different MLOps architectures, exploring the tradeoffs and benefits of each.

Overview of MLOps Architectures
Learn about the different MLOps architectures, exploring the tradeoffs and benefits of each.

Features for executives

Enterprise model library

Centrally curate and manage ML models from across your entire company

Hybrid cloud support

Run AI where and how you need it with support for CSPs, hybrid, and on-prem infrastructure

AI governance

Securely govern and de-risk AI usage with enterprise-grade controls and reports

Cross-team collaboration

Get results faster when data scientists and developers can more easily collaborate

Hardware cost reduction

Modzy's hardware management tools keep performance high while costs stay low

Military-grade security

Maintain a secure IT boundary with Modzy's FISMA moderate compliance and 100s of security controls

Learn more

Learn more about how Modzy can help you achieve a higher ROI on your investments in AI and ML.

Modzy co-founder & COO, Josh Elliot, proposes three considerations for organizations evaluating a build vs. buy strategy for AI solutions.

With AI spending projected to grow by more than 20% annually, organizations need to acquire foundational knowledge to make smart decisions about their AI life cycle.

As more enterprises push forward with their AI initiatives, it becomes critical to address these challenges with tools like MLOps.

There are three areas where MLOps vendors beat CSPs: integration support, deployment options, and infrastructure cost management.