Build Edge AI
Solutions Faster

Deploy, connect, and run machine learning (ML) models in the enterprise and at the edge, with fully managed infrastructure, tools, and workflows.

Run ML workloads anywhere–including at the edge

Consistently run ML workloads in your cloud, multiple clouds, on-prem or disconnected infrastructure. Also, run on any x86 or ARM device with low latency and increased security.

Any Edge Device

Run ML models any x86 or ARM device, with low latency results, increased security, and better networking.

Enterprise Cloud

Run your models in your cloud environment, with real-time results, full management and enterprise-grade security.

improve outcomes

One solution–endless ML use cases

A single solution for developers and data scientists to build and manage AI powered solutions using any type of model, on any data, at scale.

Any model

Machine learning, computer vision, statistical, NLP and more.

Any data type

Machine learning for accelerated analysis on text, video, audio & sensors.

Anywhere

Run anywhere, including cloud, hybrid, on-premises, embedded or edge.

Powerful and easy-to use APIs

Integrate ML workloads with powerful and easy-to-use CLIs, APIs and SDKs in popular development languages.  Explore Developer Center

Deploy

No-code / low code model deployment. Integrations for popular model training tools that data scientists love.

01

Connect

Reliable APIs and pre-built connectors for popular software solutions for fast integration.

02

Run

Execute machine learning workloads anywhere at-scale: in the cloud, on-prem, hybrid, air gap, or edge.

03

Integrates with your tech stack

Get started quickly with pre-built connectors for popular model training tools, data management solutions, CI/CD pipelines, and enterprise software solutions.

Learn about open-source

Run ML on edge devices and IoT sensors

Multi-site edge ML management

Single interface to register multiple devices and authorized models and users.

Secure edge

Integrated tools to monitor model performance and ensure model security at the edge.

Governance, security and usage controls for machine learning

Governance, security and usage controls for ML

Confidently enable teams to move fast with the monitoring, audibility, and transparency guardrails to keep the business secure and compliant.

Model monitoring, drift detection and explainability
Governance, audit, and transparency
Enterprise-grade security controls and audits
Watch the Demo

Support for ML teams, by ML experts

When you need help, we know where you're coming from and provide the support infrastructure and peer-to-peer guidance to help you reach your goals.

Community

Join the 1000+ strong Modzy Developer Community

Direct support

Speak to a product expert and get tailored support

Video tutorials

Explore all the video tutorials on YouTube

Get ML help from the experts at Modzy

Awards and Recognition

We're part of organizations building the AI-powered future.

Modzy is part of the MIT Startup ExchangeModzy is part of the Intel Ignite Accelerator programModzy is part of the NVIDIA inception programModzy is part of the Digital Manufacturing InstituteModzy recognized by GartnerModzy recognized by ForresterIDC logo

Latest from Modzy

Blog

Deploy and Run LLMs at the Edge

September 26, 2023
Learn about how LLMs can be used at the edge to generate insights for real-world use cases.
Tech Talks

AI at the Edge: Accelerating Mission-Critical Applications

September 15, 2023
Join us for a webinar where we explore integrating AI at the edge for defense applications.
Blog

Optimizing Inference with Support for the OpenVINO™ Toolkit

September 7, 2023
Modzy now supports models optimized with the OpenVINO toolkit, and the OpenVINO runtime.

download

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.

Get your questions answered and learn more about Modzy