Universal Deployment

Build and deploy any type of model, anywhere, at any scale

Security Built-In

Detect and block risky open source models and model components seamlessly

Single Platform

Stop managing multiple tools and systems for AI/ML deployments 

THE CHALLENGE

Building AI/ML involves multiple stakeholders, tools, and skills, leading to low success rates and long time to market.

The complexity and fragmentation of MLOps tools creates infrastructure hassles, increased efforts to run experiments, and less visibility and trust in what’s being delivered by Data Science and ML Engineering teams. 

THE SOLUTION

Accelerate AI pipelines with a platform built to simplify, secure, and scale MLOps. 

 JFrog ML delivers the tools, integrations, environment and out of the box approach needed for successful AI/ML development. Empower AI developers to bring new models to production fast and securely with integrated security.

“We ditched our in-house platform for JFrog ML. I Wish we had found them sooner.”

– Ryan Rollings
Principal Machine Learning Engineer, Upside

“JFrog ML… enabled us to deploy a complex feed recommendation engine within a remarkably short timeframe.”

– Asi Messica
VP Data Science, Lightricks

• Store, secure and manage ML models, datasets, and
  artifacts in a centralized repository
• Version ML artifacts for reproducibility and easy rollback
• Robust access controls for model sharing
• Scan model artifacts and dependencies for vulnerabilities
  and malicious components

• Manage every model from research to production
• Simplify experiment tracking for reproducible results
• Train and fine tune models with one click
• Deploy at any scale, from live API endpoints to Kafka
  streams
• Track model performance, drift, and data changes with
  real-time monitoring and alerts

• Prepare and manage every feature for training and
  inferenceŒ
• Reuse features across teams with a single source of truth
• Ingest and process data from any source
• Build robust feature engineering pipelines

• Work with multiple ML frameworks including
  TensorFlow, PyTorch, Scikit-learn, XGBoost
• Leverage your preferred data sources including
  Snowflake, MySQL, Kafka and moreŒ
• Fully integrated with Nvidia NIM and Hugging Face