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JFrog ML, formerly known as Qwak, is a unified MLOps platform designed to streamline the entire AI and machine learning lifecycle from development to production at scale. Built by JFrog, it addresses the complexity of managing multiple tools by providing a single platform for building, deploying, monitoring, and managing AI workflows including generative AI, large language models (LLMs), and traditional machine learning models. The platform supports model training, fine-tuning, deployment as live APIs or batch jobs, real-time monitoring, and anomaly detection. It also features a comprehensive feature store for scalable feature engineering and vector storage to enhance AI applications. JFrog ML is ideal for AI teams, data scientists, ML engineers, and product managers seeking to accelerate AI delivery, improve collaboration, and maintain operational efficiency across diverse AI projects and workflows.
4.7/5
Robust, reliable, and scalable
Intuitive and collaborative
To provide an all-in-one scalable MLOps platform that accelerates AI model development, deployment, and monitoring.
Cloud-based platform compatible with GPU/CPU infrastructure, integrates with CI/CD pipelines, Kafka streams, Slack, PagerDuty, and supports open-source models.
Flexible pricing with free trial and enterprise plans tailored to scale
Features with the highest value for users are highlighted here.
Unified MLOps platform
One-click model training and deployment
Real-time model monitoring and alerting
LLMOps with prompt management and tracing
Feature store for lifecycle management
Vector store for embedding management
Support for batch and streaming inference
Integration with collaboration and alert tools
ML Engineers
Data Scientists
AI Research Teams
Product Managers
Enterprise AI Teams
Startups
DevOps Teams
Recommendation System Developers
AI Operations Specialists
LLM Application Developers
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Enterprise
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