Managing AI Models and Datasets with Harness Artifact Registry | AI/ML Artifact Management

Building AI applications often means juggling multiple models, scattered datasets, and version chaos across local systems. But what if you could bring it all together — securely and efficiently — in one place?

In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, demonstrates how Harness Artifact Registry makes it easy to manage and govern your AI/ML assets — from models and datasets to prompts and agents — with built-in support like Hugging Face and generic registry types.

You’ll see how Harness Artifact Registry:

• Simplifies uploading, downloading, and versioning AI models and datasets
• Lets you push and pull directly from your local system
• Supports Hugging Face registry type for AI/ML models and datasets
• Enables Generic registry type for prompts, agents, and other AI artifacts
• Acts as a single source of truth for all your machine learning assets

Whether you’re working with open-source models or fine-tuned proprietary ones, Harness Artifact Registry helps you centralize, secure, and manage them with ease.

Learn more about Harness Artifact Registry:
🔗 Product page – https://harness.io/products/artifact-registry

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