Predictive Content Generator¶
Availability information
The Predictive Content Generator application template requires GenAI and MLOps functionality. If you do not currently have access to these features, sign up a 14-day DataRobot trial to try out this template.
Access this application template on GitHub
Generate prediction content using Prediction Explanations from a classification model. This application template returns natural language-based personalized outreach. Real world use cases for this technology include:
- Using a next-best-offer predictive model to automatically draft personalized promotions.
- Using a credit risk model to automatically draft approval and rejection letters.
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.
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Start building in minutes: Deploy complete AI applications instantly, then customize AI logic or front-end independently - no architectural rewrites needed.
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Keep working your way: Data scientists keep working in notebooks, developers in IDEs, and configs stay isolated - update any piece without breaking others.
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Iterate with confidence: Make changes locally and deploy with confidence - spend less time writing and troubleshooting plumbing, more time improving your app.
Key features¶
- Best-in-class predictive model training and deployment using DataRobot AutoML.
- Governance and hosting predictive and generative models using DataRobot MLOps.
- A shareable and customizable front-end for interacting with both predictive and generative models.
Warning
Application templates are intended to be starting points that provide guidance on how to develop, serve, and maintain AI applications. They require a developer or data scientist to adapt and modify them for their business requirements before being put into production.
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:
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AI logic: Necessary to service AI requests, generate predictions, and manage predictive models.
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App logic: Necessary for user consumption, whether via a hosted front-end or integrating into an external consumption layer.
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Operational logic: Necessary to turn on all DataRobot assets.