Predictive AI Starter¶

Access this application template on GitHub

Execute a basic Predictive AI deployment workflow in DataRobot. This template is ideal for kickstarting new recipes, providing a simple "hello world" example that can be easily customized to fit specific use cases.

App templates transform your AI projects from notebooks to production-ready applications. Getting models into production often means rewriting code, juggling credentials, and coordinating with multiple tools and teams just to make simple changes. DataRobot's composable AI apps framework eliminates these bottlenecks, letting you spend more time experimenting with your ML and app logic, and less time wrestling with plumbing and deployment.

• Start building in minutes: Deploy complete AI applications instantly, then customize AI logic or front-end independently—no architectural rewrites needed.

• Keep working your way: Data scientists keep working in notebooks, developers in integrated development environments (IDEs), and configs stay isolated—update any piece without breaking others.

• Iterate with confidence: Make changes locally and deploy confidently—spend less time writing and troubleshooting plumbing, and more time improving your app.

Key features¶

• Hosted and shareable user interface that generates personalized outreach and is easy to deploy.
• DataRobot best-in-class AutoML that leverages cutting-edge AutoML capabilities to predict and tailor outreach messaging for each client.
• DataRobot MLOps hosting, monitoring, and governing of back-end deployments to ensure robust and reliable operations.

Architecture¶

Each template provides an end-to-end AI architecture, from raw inputs to deployed application, while remaining highly customizable for specific business requirements.

App templates contain three families of complementary logic. For this template, you can opt-in to fully custom AI logic and a fully custom front-end or utilize DataRobot's off-the-shelf offerings:

• AI logic: Necessary to service AI requests, generate predictions, and manage predictive models.

• App logic: Necessary for user consumption, whether via a hosted front-end or integrating into an external consumption layer.

• Operational logic: Necessary to turn on all DataRobot assets.