JFrog Integrates the JFrog Platform with NVIDIA Enterprise AI Factory to Accelerate Agentic AI
- Inno-Thought Team
- Jun 3
- 4 min read
Updated: Jun 23
New Full-Stack, Validated Design Aims to Accelerate AI/ML Model Engineering, Security, Operations and Delivery for the AI-powered Enterprise
JFrog Ltd (Nasdaq: FROG), the Liquid Software company and creators of the award-winning JFrog Software Supply Chain Platform, recently announced the integration of its foundational DevSecOps tools with the NVIDIA Enterprise AI Factory validated design. JFrog will serve as the cornerstone software artifact repository and secure model registry for the landmark agentic AI architecture.
Following a successful NVIDIA NIM integration with the JFrog Platform, this new collaboration delivers a full-spectrum MLOps solution, designed to ensure scalable, secure and seamless deployment of AI-powered applications using the NVIDIA Blackwell platform.
“The future of AI depends not only on innovation – but on trust, control, and seamless execution,” said Shlomi Ben Haim, CEO and co-founder of JFrog. “To deliver AI at scale, enterprises need to adopt the same concepts applied to software: developer-friendly workflows, strong security, robust governance, and full lifecycle management. ML models are binaries, and they must be managed as first-class software artifacts. That’s why we’re excited to partner with NVIDIA to bring JFrog’s Software Supply Chain Platform as the single source of truth for all software and AI assets to the NVIDIA Enterprise AI Factory so organizations can build and scale trusted AI solutions with confidence.”
Delivering Critical Infrastructure to Enable Future AI Innovation
The JFrog Platform provides customers with a “single source of truth” for software components within NVIDIA Enterprise AI Factory, which contains an integrated and validated suite of software technology solutions enterprises can use to develop, deploy, and manage agentic AI, physical AI, and HPC workloads on-premises. This validated design aims to allow organizations to have full control of their data and operate advanced AI agents in a secure environment. Key capabilities include:
Secure & Governed Software Component Visibility: Enables all ML models, engines, and software artifacts to be scanned for security issues, versioned, governed, and traceable across the entire software development lifecycle.
End-to-End Software Artifact & ML Model Management: Enables the seamless pulling, uploading, and hosting of AI models and datasets, AI containers, Docker containers, and dependencies optimized for the NVIDIA Enterprise AI Factory validated design.
Rapid, Trusted AI/ML Application Provisioning in Runtime: Simplifies configuration of AI environments by eliminating the need for runtime environments to pull components from outside of the organization, thanks to the universality, proven scalability and robustness of JFrog Artifactory.
Future-proofed for Evolving GenAI Applications: Quickly and easily manages ML model versioning and upgrades to new and approved model generations.
“Enterprises building AI factories need to manage the complexity of AI adoption while ensuring performance, governance and trust,” said Justin Boitano, Vice President, Enterprise AI Software Products, NVIDIA. “JFrog’s unified software supply chain platform, paired with the NVIDIA Enterprise AI Factory validated design, enables rapid, responsible AI innovation at scale.”
The integration is designed to enable the JFrog Platform to run natively on NVIDIA Blackwell systems to help reduce latency and process tasks with unparalleled performance, efficiency, and scale. It supports a wide range of AI-enabled enterprise applications, agentic and physical AI workflows, autonomous decision-making, and real-time data analysis across various industries, including financial services, healthcare, telecommunications, retail, media, and manufacturing. Additionally, the system leverages NVIDIA’s engineering know-how and partner ecosystem to help enterprises accelerate time-to-value and mitigate the risks of AI deployment.
Related Resources
Whitepaper+Webinar : Hungry for More Software Supply Chain Risks, Trends, and Insights?
Key takeaways you will get from this report / event :
Open-source risk is exploding with MILLIONS of new packages
CVE data issues obfuscate vulnerability severity and applicability
Organizations continue to increase the number of security tools used
Complete visibility of software provenance eludes many organizations
The AI software supply chain is booming, but so is the risk
不同企業在開發軟體時常常會遇到以下困境 :
軟體交付流程混亂：如果公司的軟體交付流程缺乏統一的管理和控制，可能會導致混亂和效率低下。例如，手動管理依賴、軟體版本和佈署流程可能會導致錯誤和延遲。
安全漏洞風險：缺乏強大的安全性措施可能會使公司容易受到安全漏洞的影響。如果沒有有效的漏洞管理和控制機制，公司的軟體供應鏈可能會受到威脅，這可能會導致資料泄露或其他安全問題。
版本控制困難：如果公司在管理軟體版本方面遇到困難，如無法有效跟蹤和Rollback版本變更，可能會導致混亂和不一致。這可能會影響開發人員的工作效率，並導致影響軟體品質問題或者是影響到服務對象的使用。
持續集成/持續佈署（CI/CD）瓶頸：如果公司的CI/CD流程不夠自動化和靈活，可能會成為開發和佈署的瓶頸。例如，手動執行測試、構建和佈署流程可能會導致長時間的交付週期和不可預測的交付結果。
雲端化挑戰：對於那些正在採用雲端和混合雲解決方案的公司來說，將應用程式佈署到多個雲環境中可能會帶來挑戰。缺乏跨雲管理和一致性可能會導致佈署和運營的困難。
使用JFrog解決困境
JFrog提供了一個完善的軟體供應鏈管理平台，支援軟體建置、交付和自動化。
以JFrog Artifactory為核心,我們在整個DevOps和軟體供應鏈中策劃安全和單一的記錄來源。
JFrog透過自動化、情境分析和增強修復，有效地偵測和修復 DevOps Pipeline中的安全問題。
JFrog作為安全軟體供應鏈的一部分，提供完善的SBOM報告。
JFrog支援在自主機、雲端和多雲環境中的工具選擇佈署的目標。
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