JFrog ML
JFrog ML: A centralized registry for teams that need governed, versioned model delivery. Ranked #6 of 34 in Model Registry Software by our editors (8.6/10); pricing: Pricing on request; best for teams prioritizing secure model supply chains.
At a glance
- Editor score8.6 / 10
- PricingPricing on request
- Best forTeams prioritizing secure model supply chains
- Free planNo
- Founded2008 · Sunnyvale, California, and Netanya, Israel
- Facts checked22 Sep 2026
Where it wins
- Immutable model and artifact versioning through JFrog Artifactory
- Canary, A/B, and shadow deployment strategies
- Security scanning with JFrog Xray and approval governance
Where it doesn't
- No free plan
- Pricing requires contact with sales
- Broader MLOps scope may exceed registry-only needs
Our verdict on JFrog ML
JFrog ML is an MLOps platform for data scientists, ML engineers, AI developers, and DevOps teams. Its centralized model registry supports the path from research to production, with model building, training, testing, packaging, deployment, monitoring, feature pipelines, and governance. Models can be versioned as immutable artifacts in JFrog Artifactory and deployed as real-time API endpoints, batch jobs, or streaming applications. The platform is available through web, API, and self-hosted options, including JFrog’s cloud and hybrid architecture.
The registry’s main strength is its connection to controlled model delivery. JFrog ML supports model and artifact versioning, deployment tracking, approval and allow-list governance, and monitoring with performance metrics, anomaly detection, and alerts. Teams can choose canary, A/B, or shadow deployment strategies, while model training and fine-tuning can run on CPU or GPU infrastructure. Integrations with JFrog Artifactory, JFrog Xray, Slack, and PagerDuty support artifact management, security scanning, and operational notifications. This makes it a fit for organizations that want model lifecycle controls alongside an existing JFrog environment.
According to the vendor’s pricing page, Unified MLOps and Ultimate MLOps are available through specified Enterprise subscriptions, with pricing handled through contact with sales. Both listed plans include Model Registry. There is no free plan. JFrog ML is best suited to teams that need governed supply chains, immutable storage, deployment controls, and security scanning across model artifacts and dependencies. Teams seeking only a lightweight registry, a free starting tier, or a narrowly focused catalog may prefer a simpler alternative.
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JFrog ML pricing
All 2 JFrog ML plans and prices →
JFrog ML fact sheet
| Free plan | No |
|---|---|
| Paid from | Not verified |
| Model versioning | Yes |
| Approval workflows | Not verified |
| Model lineage | Yes |
| Deployment tracking | Yes |
| Model aliases | Not verified |
| Artifact storage | Yes |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Support | Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 4 integrations: PagerDuty, Slack, JFrog Artifactory, JFrog Xray |
| Pricing | Pricing on request (source) |
| Website | jfrog.com |
| Facts checked | 22 Sep 2026 |
JFrog ML integrations
JFrog ML lists 4 integrations on its own site.
- PagerDuty
- Slack
- JFrog Artifactory
- JFrog Xray
Alternatives to JFrog ML
- SAS Model ManagerA governance-focused registry for managing models from versioning through monitoring.9.3
- Cloudera AI RegistryA focused model registry for teams operating machine learning workflows in Cloudera AI.9.2
- MLflow Model RegistryAn open registry for versioning, lineage, approvals, aliases, and model promotion.8.9
See all JFrog ML alternatives →
JFrog ML vs the competition
- JFrog ML vs SAS Model Manager
- JFrog ML vs Cloudera AI Registry
- JFrog ML vs MLflow Model Registry
- JFrog ML vs W&B Registry
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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