# Predictive AI Starter
URL: https://docs.datarobot.com/en/docs/wb-apps/app-templates/at-ai-starter.html

> Outlines a basic predictive AI deployment workflow in DataRobot using a Streamlit front-end.

# Predictive AI Starter

> [!NOTE] Availability information
> The Predictive AI Starter application template requires MLOps functionality. If you do not currently have access to this feature, sign up a 30-day [DataRobot trial](https://www.datarobot.com/trial/?utm_source=productbanner&utm_medium=web&utm_campaign=FreeTrial23productcta) to try out this template.

[Access this application template on GitHub](https://github.com/datarobot-community/predictive-ai-starter)

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

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

> [!WARNING] 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.

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