Deploy and manage AI workflows from development to production at scale
JFrog ML (formerly Qwak) is a unified platform that helps teams build, deploy, and monitor AI applications efficiently. It handles everything from classic machine learning to cutting-edge LLMs and GenAI projects. The platform simplifies collaboration between technical teams while automatically handling infrastructure scaling, letting developers focus on creating business value rather than DevOps tasks.
One-click deployment for live APIs, batch, or streaming inference
Pre-optimized open-source models like Llama 3 ready for deployment
Track model performance and data anomalies with Slack/PagerDuty alerts
Version-controlled prompt registry with team collaboration features
Large-scale embedding storage for RAG pipelines and recommendations
This tool is best for:
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JFrog ML can be integrated with these apps and services:
Recent data shows that JFrog ML has 46.7K monthly visits (85.2% increase from the previous month), 39.0% bounce rate, and average 2.42 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by United States contributing 16% of total traffic. SEO performance is shown by 5 tracked keywords, with "qwak" being the top-performing keyword with 200 monthly searches. See below for more info.
Monthly Visits
46.7K
Pages per Visit
2.42
Bounce Rate
39.0%
Average Time on Site
55s
| SEO Keyword | Volume | CPC |
|---|---|---|
| qwak | 200 | - |
| research engineer vs ml engineer | 220 | - |
| "etl" feature store | 140 | - |
| how to deploy a python model into production | 100 | - |
| ml pipeline | 3.1K | $2.84 |
| Source | Traffic Share |
|---|---|
| Direct | 35% |
| Search | 50% |
| Social | 4% |
| Referrals | 10% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 16% |
 | 15% |
 | 12% |
 | 7% |
 | 7% |
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