DataRobot AI Platform overview¶

What is DataRobot?¶

The DataRobot AI Platform provides a unified experience for building, governing, and monitoring enterprise AI.

What solutions does DataRobot offer?¶

The application is organized by stages in the AI lifecycle: Build, govern, operate.

Build¶

Building great AI solutions—both generative and predictive—requires a lot of experimentation. Use Workbench to quickly experiment, easily compare across experiments, and organize all your experiment assets in an intuitive Use Case container.

Govern¶

Use Registry to create deployment-ready model packages and create compliance documentation for the purposes of enterprise governance.

Registry ensures that all your AI assets are documented and under version control. With test results and metadata stored alongside each AI asset, you can deploy models to production with confidence, regardless of model origin—whether DataRobot models, user-defined models, or external models.

Operate¶

Use Console to view the operating status of each deployed model.

As your organization becomes more AI-driven, you’ll have tens or even hundreds of task-specific models. Console provides a centralized hub for observing the performance of these models, allowing you to configure numerous automated intervention and notification options to keep things running smoothly.

One-click deployments¶

But where do deployments fit into the structure above? The deployment process is your model's seamless transition from Registry to Console. Once the model is registered and tested in Registry, you’ll have the option to deploy it with a single click.

Once you click to deploy, DataRobot’s automation creates an API endpoint for your model, in your selected prediction environment, and configures all the observability and monitoring.

All four of these deployment options are supported:

• A DataRobot model to a DataRobot prediction server.
• A DataRobot model to an external prediction server.
• A custom model to a DataRobot prediction server.
• A custom model to an external prediction server.

Generative AI¶

DataRobot's generative AI offering builds off of DataRobot's predictive AI experience to provide confidence scores and enable you to bring your favorite libraries, choose your LLMs, and integrate third-party tools. You can embed or deploy AI wherever it will drive value for your business, and leverage built-in governance for each asset in the pipeline.

Inside DataRobot there is very little distinction between generative and predictive AI. But, you will find that many tutorials and examples are organized along these lines.

• Predictive AI includes time series, classification, regression, and unsupervised machine learning such as anomaly detection and clustering.
• Generative AI (GenAI) includes text and image generation using foundational models.

Generative AI in DataRobot

Which experience should you choose?¶

When working in DataRobot, you have two interface choices:

1. Log into the app via web browser and work with the graphical user interface (UI)—either NextGen or DataRobot Classic.
2. Access it programmatically, with the REST API or Python client packages.

If you're leaning towards using DataRobot programmatically, it's recommended that you explore the workflows in the UI first. DataRobot is committed to full accessibility in both interfaces, so you are not locked into a single choice. Know that you can:

• Flexibly switch between code and UI at any time.
• Seamlessly collaborate with other users who are working with a different option.
• When in code, use any development environment of your choice.

NextGen¶

An intuitive UI-based product comprised of Workbench for experiment based iterative workflows, Registry for model evolution tracking and the centralized management of versioned models, and Console for monitoring and managing deployed models. NextGen also provides the gateway for creating GenAI experiments, Notebooks, and apps.

Open Workbench in 5

Code¶

A programmatic alternative for accessing DataRobot using the REST API or Python client packages.

Open Code in 5

Classic¶

The original UI-based, value-driven AI product. It provides a complete AI lifecycle platform, leveraging machine learning that has broad interoperability and end-to-end capabilities for ML experimentation and production. DataRobot Classic is being migrated to the new user interface, NextGen.

Open DataRobot Classic in 5

Where to get help¶

Help is everywhere you look:

Next steps¶

So what's next? The best way to learn DataRobot is hands-on. Investing an hour to complete these two suggested exercises could save you countless hours of clicking and searching.