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SPECIFICTION
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JFrog ML

jfrog.com

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Spec score 7.9 #7 of 36 in Model Registry Software

Spec sheet

Purpose
JFrog ML is a unified platform for building, deploying, and monitoring machine learning models in production.Read 2 Oct 2026 · docs.jfrog.com
Product
JFrog ML is an all-in-one solution to build, deploy, manage, and monitor AI workflows, from GenAI and LLMs to classic machine learning.Read 3 Oct 2026 · jfrog.com
Audience
The product is intended for data scientists, ML engineers, and AI developers bringing AI and ML services into production.Read 3 Oct 2026 · jfrog.com
Deployment
Models can be served as API endpoints, used for batch inference, and A/B tested.Read 3 Oct 2026 · jfrog.com
Integrations
JFrog's integration catalog includes Hugging Face, NVIDIA, Amazon SageMaker, and Azure Machine Learning integrations.Read 3 Oct 2026 · jfrog.com
Headquarters
Sunnyvale, California, and Netanya, IsraelRead 28 Sep 2026 · jfrog.com
Founded
2008Read 28 Sep 2026 · jfrog.com
Company
JFrog says its Liquid Software journey began in 2008; an official JFrog-hosted company profile lists its founding year as 2008 and headquarters in Netanya, Israel, and Sunnyvale, California.Read 3 Oct 2026 · jfrog.com
Alerts
JFrog ML alerting documentation describes integrations with Slack, Opsgenie, and PagerDuty for model and feature-set alerts.Read 3 Oct 2026 · docs.jfrog.com
Certifications
JFrog's Trust Certificate Program lists SOC 2 Type II, SOC 3, IRAP, ISO 27001, ISO 27701, ISO 27017, TISAX, CSA STAR Level 1, Cyber Essentials, and KY3P by S&P Global.Read 3 Oct 2026 · jfrog.com
Cloud providers
The product page states that JFrog ML natively supports AWS, Google Cloud, and Microsoft Azure.Read 2 Oct 2026 · jfrog.com
Clouds
JFrog ML states native support for AWS, Google Cloud, and Microsoft Azure, with deployment on JFrog's platform or customer infrastructure.Read 3 Oct 2026 · jfrog.com
Deployment options
JFrog ML Cloud offers cloud deployment, while its hybrid architecture allows data and models to remain in a customer's cloud environment.Read 2 Oct 2026 · docs.jfrog.com
Feature pipelines
JFrog ML supports batch, streaming, and real-time feature transformations with end-to-end pipeline visibility.Read 2 Oct 2026 · docs.jfrog.com
Feature Store
The Feature Store supports batch, streaming, and real-time feature sets, but JFrog ML SaaS supports batch feature sets only; real-time and streaming feature sets require a hybrid deployment.Read 3 Oct 2026 · docs.jfrog.com
Lifecycle
The platform supports data preparation, model building and training, deployment, monitoring, and pipeline automation.Read 2 Oct 2026 · docs.jfrog.com
MLOps bundle eligibility
The pricing page says Unified MLOps is available for Enterprise X and Enterprise + subscriptions, while Ultimate MLOps is available for Enterprise + subscriptions.Read 2 Oct 2026 · jfrog.com
Model deployment
Models can be deployed as REST endpoints, batch transformation jobs, or streaming applications.Read 2 Oct 2026 · docs.jfrog.com
Model registry
JFrog ML uses Artifactory as a model registry for versioning, traceability, and governance, and describes Xray scanning models, containers, and artifacts for vulnerabilities and license compliance issues.Read 3 Oct 2026 · docs.jfrog.com
Model training
The product page says users can train or fine-tune models, including building models from scratch.Read 2 Oct 2026 · jfrog.com
Observability
Its production observability features include performance metrics, model feature management, and inference analysis and queries.Read 2 Oct 2026 · docs.jfrog.com
Production testing
JFrog ML supports gradual model deployment and A/B testing in production.Read 2 Oct 2026 · docs.jfrog.com
Security and governance
JFrog describes JFrog ML as bridging AI/ML and DevSecOps and bringing AI development into an existing secure software development lifecycle.Read 2 Oct 2026 · jfrog.com
Security controls
JFrog's self-managed AI/ML service uses a frontend on the customer's JFrog Platform instance and a backend hosted by JFrog; enabling it requires a direct internet connection to bridge.ml.frog.io and an Enterprise+ license with AI Catalog entitlement.Read 3 Oct 2026 · docs.jfrog.com
Supported audiences
JFrog ML is presented for data scientists, ML engineers, and AI developers taking AI and ML services to production.Read 2 Oct 2026 · jfrog.com
Training
JFrog ML supports model training and deployment, fine-tuning models or building them from scratch, LLM applications, prompt engineering, and feature lifecycle management.Read 3 Oct 2026 · jfrog.com
Usage limits
The pricing page lists Unified MLOps with a 200-developer base bundle and Ultimate MLOps with a 500-developer base bundle, with additional developers available at volume discounts.Read 2 Oct 2026 · jfrog.com

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