# Predictions in mobile apps

> Predictions in mobile apps - Learn how to incorporate DataRobot predictions into a mobile app.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.581769+00:00` (UTC).

## Primary page

- [Predictions in mobile apps](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-building-tuning/pred-mobile.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Model building and fine-tuning](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-building-tuning/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/tree/main/use_cases_and_horizontal_approaches/using-datarobot-in-mobile-apps)

An AI model can't just be an experiment. AI Predictions need to be in the hands of real users interactive with customers, products, or users. This accelerator demonstrates how to incorporate DataRobot predictions into a mobile app.

Included in this accelerator is a Swift Playground App prototype. The playground integrates an app that uses the Iris dataset and calls a DataRobot model to predict the likely sub-species of Iris plant.