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Try NowWhat is JFrog ML?
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.
AI Tool Review Summary
4.7/5
Robust, reliable, and scalable
Intuitive and collaborative
LLMNLPMachine LearningVector Search
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
How It Works
1
Build and Train Models
Create and fine-tune machine learning or LLM models using GPU or CPU resources with one-click training.
2
Deploy at Scale
Deploy models as live APIs, batch jobs, or streaming endpoints with multi-version support.
3
Monitor and Manage
Track model performance, detect anomalies, and receive alerts via integrations like Slack and PagerDuty.
4
Collaborate and Iterate
Use shared feature stores, prompt registries, and workflow tracing to enhance team collaboration and model refinement.
ML Engineers
Data Scientists
AI Research Teams
Product Managers
Enterprise AI Teams
Startups
DevOps Teams
Recommendation System Developers
AI Operations Specialists
LLM Application Developers
Free Trial
$0/free
Full platform access for limited time Basic support Access to model training and deployment
Popular
Enterprise
$Custom pricing/monthly
Unlimited model deployments Advanced monitoring and alerting Dedicated support Feature store and vector DB Multi-cloud support
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Claim this tool to manage plans, pricing, and listing details.
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
Pros & Cons
Simplifies end-to-end AI workflow management in one platform. Supports scalable deployment of diverse model types including LLMs.
May require onboarding time to fully leverage advanced features. Primarily targeted at enterprise-level teams, possibly complex for smaller projects.
FAQs
Just Launched
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