# Build intelligent Android apps: Cloud and hybrid inference

DevFeed: [Build intelligent Android apps: Cloud and hybrid inference](<https://devfeed.tech/articles/build-intelligent-android-apps-cloud-and-hybrid-inference-22680.md>)

Original publisher: [Read original article](<http://android-developers.googleblog.com/2026/07/build-intelligent-android-apps-cloud-hybrid-inference.html>)

Author: Android Developers (noreply@blogger.com)

Published: 2026-07-21T13:00:00Z

Content type: tutorial

Language: en

Sources: [Android Developers Blog](<https://devfeed.tech/sources/android-developers-blog-3.md>)

Topics: [Android](<https://devfeed.tech/topics/android.md>), [Firebase](<https://devfeed.tech/topics/firebase.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [ML Kit](<https://devfeed.tech/topics/ml-kit.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [android](<https://devfeed.tech/tags/android.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [firebase-ai-logic](<https://devfeed.tech/tags/firebase-ai-logic.md>), [gemini](<https://devfeed.tech/tags/gemini.md>), [grounding](<https://devfeed.tech/tags/grounding.md>), [hybrid-inference](<https://devfeed.tech/tags/hybrid-inference.md>), [inference](<https://devfeed.tech/tags/inference.md>), [on-device](<https://devfeed.tech/tags/on-device.md>)

## AI overview

This tutorial explains how to build cloud-hosted and hybrid AI features in Android apps with Firebase AI Logic. Using the Jetpacker app as an example, it covers web-grounded museum assistance, hybrid restaurant review drafting with Gemini Nano and cloud fallback, and custom-routed live translation for hotel support.

## Source excerpt

Posted by Thomas Ezan, Jolanda Verhoef, Caren Chang, Senior Developer Relations Engineers, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we explored how to build intelligent on-device features using Gemini Nano through ML Kit's Prompt API. In this post, we will look at how you can leverage Firebase AI Logic to build cloud-hosted and hybrid AI features: Grounding answers in real-world context Routing requests dynamically between cloud and local execution using hybrid inference Translating content with custom routing systems Sometimes a use case requires AI models with greater world knowledge, a much larger context window, or the ability to handle complex queries. In those scenarios, we can leverage cloud models. Other times, you want the best of both worlds: using hybrid inference to run on-device when available to lower costs, while falling back to the cloud to ensure compatibility for all devices. Cloud and hybrid features in Jetpacker: Museum assistant with web grounding, hybrid restaurant review drafting, and support chat featuring custom-routed live translation. Let's look at how we implemented three cloud and hybrid features in Jetpacker: a museum assistant with web grounding hybrid restaurant review drafting hotel support chat featuring custom-routed live translation. Use LLM grounding for up-to-date informationMuseum assistant chatbot with LLM grounding The Museum assistant is an interactive chatbot designed to help users plan their museum visits. It provides visitors with up-to-date details regarding specific exhibits, current opening hours, ticket pricing, and more. Museum assistant is a chatbot that answers questions, such as 'How can I get a ticket discount for Le Louvre?' When building AI features, getting the model to answer with fresh, accurate, and specific real-world info