What is AI Applications?

AI Applications lets developers, even those with limited machine learning skills, tap into the power of Google's foundation models, search expertise, and conversational AI technologies to create enterprise-grade generative AI applications for search, recommendations, and conversation agents.

The product AI Applications essentially packages the following aspects together:

Vertex AI Search: Search and recommendation apps, used for AI-enabled search, browse, grounded answer generation, and recommendations. See Vertex AI Search.
Dialogflow conversational agents: Conversational Agents, used for creating AI-driven conversational user interfaces, was originally available as part of AI Applications. In early 2025, these products have become distinct offerings. See the Conversational Agents documentation.

This user guide talks about Vertex AI Search and all its offerings in detail.

Vertex AI Search

Vertex AI Search is a fully-managed platform, powered by large language models, that lets you build AI-enabled search and recommendation experiences for your public or private websites or mobile applications.

Information retrieval using AI and LLMs

Vertex AI Search brings together the power of deep information retrieval, state-of-the-art natural language processing, and the latest in large language model (LLM) processing to understand user intent and return the most relevant results for the user.

With Vertex AI Search, you can build a Google-quality search app on data you control. You also have the option to use the search results that you retrieve to ground generative AI LLM responses. For more information, see the blog post Your RAG powered by Google Search.

With recommendations, you can build a recommendations app across your data that suggests content similar to the content that the user is viewing.

An easy experience to get started

Vertex AI Search makes it easy to get started with high-quality search or recommendations based on data that you provide. As part of the setup experience, you can:

Use your existing Google Account or sign up for one.
Use your existing Google Cloud project or create one.
Create an app and attach a data store to it. Provide data to search or recommend by entering the URLs for your website content, importing your data from BigQuery or Cloud Storage, or importing FHIR R4 data from Cloud Healthcare API, or uploading through RESTful CRUD APIs. Syncing data from third-party data sources is available in Preview with allowlist. For more information, see About apps and data stores
Embed JavaScript widgets and API samples to integrate search or recommendations into your website or applications.

Search apps

With Vertex AI Search, you can quickly build a Google-quality search app on your own data and embed a search bar in your web pages or app.

You can create the following different types of search apps:

Custom search. Apply custom search to websites or to data stores containing your proprietary data, giving your customers Google-quality search experiences on the content that you want them to see. For more information, see Introduction to custom search and Get started with custom search.
Media search. This is a search capability specially designed for media content such as movies, videos, and music. With media search, audiences can efficiently find the media content that they want to view or listen to. For more information, see Introduction to media search and recommendations and Get started with media search.
Healthcare search. This is a search capability that lets you query healthcare records stored in FHIR data stores. You can import FHIR resources that contain clinical data from your Cloud Healthcare API FHIR store. You can also search unstructured data, such as images, PDF files, and RTF files, referenced by the FHIR resources.

Recommendation apps

You can quickly build a state-of-the-art recommendations app on your own data that can suggest content similar to the content that the user is viewing.

You can create the following two different types of recommendations apps:

Media recommendations. Get recommendations for media content such as videos, news, and music. With media recommendations, audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives. For more information, see Get started with media recommendations.
Custom recommendations (Preview). Get recommendations for non-media content. For more information, see Get started with custom recommendations.

Note: This feature is a Preview offering, subject to the "Pre-GA Offerings Terms" of the GCP Service Specific Terms. Pre-GA products and features may have limited support, and changes to pre-GA products and features may not be compatible with other pre-GA versions. For more information, see the launch stage descriptions. Further, by using this feature, you agree to the Generative AI Preview terms and conditions ("Preview Terms"). For this feature, you can process personal data as outlined in the Cloud Data Processing Addendum, subject to applicable restrictions and obligations in the Agreement (as defined in the Preview Terms).

Key features

Out-of-the-box natural language understanding and semantic search. Get a high-quality search experience without needing to implement and maintain systems that perform keyword searches or pattern matching.
Out-of-the-box capabilities to understand synonyms, correct spellings, and auto-suggest searches. Improve the user's search experience without the need to implement complex natural language processing techniques.
Generative AI. Get generative AI-powered summarization and conversational search for unstructured documents.
Out-of-the-box recommendations. Get state-of-the art, ML-based content and metadata understanding that lets your users quickly find content that is similar to the content that they're viewing.
AI Applications console and APIs. Use the AI Applications page of the console or Google's APIs to set up a search app for your public websites or for your structured or unstructured data.
Out-of-the-box widget. Integrate search into your website. For more information, see Add the search widget to a web page.
Self learning. Get self-learning ranking models and advanced analytics. This requires the user's clickstream.
Optimization for media. Create recommendation and search apps optimized for media content.
Natural language querying of healthcare data. Search FHIR resources without prior knowledge of any query language.
Context-aware healthcare searches. Find search results with semantic relevance that a structured FHIR search might miss.

Google Cloud console or the API?

You can implement Vertex AI Search in any of the following ways:

Use the Google Cloud console. Use the AI Applications page of the console for a quick-start experience using a web interface. From the console, you can create your search app, import your data, test the user experience, and view analytics.
Use the AI Applications API. Use the AI Applications API when you're ready to integrate search or recommendations into your website or applications.
Use both the Google Cloud console and the API. You can set up your app and import your data using the console, for example, and then use the API to test the user experience and integrate it into your website or application.