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Google Maps
OpenAI (ChatGPT, Whisper)

Connect Google Maps and OpenAI (ChatGPT, Sora, DALL-E, Whisper) integrations

Explore ready-made Google Maps and OpenAI (ChatGPT, Whisper) templates and start automating in minutes.

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Create a custom workflow

Transform your location data into powerful AI-driven insights by connecting Google Maps with OpenAI (ChatGPT, Sora, DALL-E, Whisper) through automated workflows. Every new coordinate or location event instantly triggers intelligent actions—generating rich descriptions, creating custom visualizations, or processing voice notes—turning geographic data into actionable content automatically.

Create a custom workflow

Every automation starts with a trigger and an action. Select one from each app to generate a workflow tailored to your needs.

OpenAI (ChatGPT, Whisper)
Trigger: Watch batch completed
Google Maps
Action: Select an action
1. Select a trigger

  • Triggers when a batch is completed.

2. Select an action

  • Gets the details of a location by either input address or geocodes.

  • Returns an static image (PNG or JPG) of Google Map.

  • Gets the details of a timezone by geographical coordinates.

  • Provides elevation data for all locations on the surface of the earth, including depth locations on the ocean floor by input geographic coordinates

  • Performs an arbitrary authorized API call.

Select a trigger and an action

Create workflow (opens in a new tab)

Triggers and actions

Connect OpenAI (ChatGPT, Sora, DALL-E, Whisper) as a trigger and Google Maps as an action through Make's integration platform. When OpenAI (ChatGPT, Sora, DALL-E, Whisper) detects new location data or coordinates, it triggers automated workflows that send this geographic information to OpenAI's tools as actions. For example, new OpenAI (ChatGPT, Sora, DALL-E, Whisper) coordinates can automatically trigger ChatGPT to generate detailed location descriptions, activate DALL-E to create custom map visualizations based on geographic data, or prompt Whisper to process location-related voice notes. This trigger-action integration enables you to automatically add AI-generated insights to location data, create visual content based on geographic information, and build intelligent workflows where OpenAI (ChatGPT, Sora, DALL-E, Whisper) events trigger OpenAI's advanced AI capabilities to perform specific actions.

Analyze images (Vision)
Analyzes images according to specified instructions.
Action
Cancel a batch
Cancels an "in-progress" batch. The batch will be in status "cancelling" for up to 10 minutes, before changing to "cancelled", where it will have partial results (if any) available in the output file.
Action
Create a batch
Creates and executes a batch of API calls.
Action
Create a skill
Creates a new skill.
Action
Create a skill version
Creates a new immutable skill version.
Action
Create a vector store or add files
Creates a new vector store and optionally adds files to it, or adds files to an existing vector store.
Action
Delete a conversation
Deletes an existing conversation.
Action
Delete a response
Deletes an existing model response.
Action
Delete a skill
Deletes a skill. This action cannot be undone.
Action
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How to set up Google Maps and OpenAI (ChatGPT, Whisper) in 5 easy steps

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Step 1

Set up your Google Cloud Platform project

Before you can use Google Maps with Make, you need to create a project in Google Cloud Platform. Log in, click to create a new project, give it a name, and you're ready to go. This project serves as the bridge that allows Make to securely communicate with Google Maps services.

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Step 2

Enable billing and activate Google Maps APIs

To use Google Maps features, you'll need to set up billing in your Google account and then enable the specific Google Maps APIs you want to use. Navigate to the APIs Library in your Google Cloud project and activate the mapping features you need, such as directions or place searches. This gives your project permission to access these Google Maps capabilities.

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Step 3

Generate your Google Maps API key

An API key is like a password that lets Make connect to your Google Maps account. In Google Cloud Platform, go to the Credentials section, create a new API key, and copy it to a safe place. This unique key is what you'll use to authenticate your connection in Make.

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Step 4

Connect Google Maps to your Make scenario

Log in to Make and open the workflow where you want to use Google Maps. Add a Google Maps module and click to create a connection, then give your connection a descriptive name and paste in the API key you created earlier. Click Save to establish the connection between Make and Google Maps.

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Step 5

Configure your Google Maps action

Once connected, select what you want Google Maps to do in your automation, such as finding directions, searching for places, or calculating distances. Fill in the necessary details like addresses or locations, and Make will retrieve the information you need from Google Maps to complete your workflow.

Transform location data into intelligent insights with AI-powered automation

Combine Google Maps with OpenAI capabilities to generate smart location analysis, natural language directions, visual content through DALL-E, and automated geographic insights using ChatGPT.

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AI-powered location intelligence

Automatically analyze and extract insights from Google Maps data using ChatGPT to generate summaries, recommendations, and detailed reports about locations, routes, and geographic information.

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Intelligent route descriptions

Transform complex route data from Google Maps into natural language directions and travel narratives using OpenAI's language models for better user communication.

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Automated geographic content creation

Generate location-based marketing content, business descriptions, and travel guides by combining Google Maps place data with ChatGPT's creative writing capabilities.

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Smart address processing

Use OpenAI to parse, validate, and enrich unstructured address data before geocoding with Google Maps, improving data quality and mapping accuracy.

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FAQs

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By connecting Google Maps with OpenAI through Make, you can automate complex location-based workflows such as generating intelligent route descriptions, creating personalized travel itineraries, analyzing geographic data with AI insights, or automatically generating location-based content for marketing. For example, you could use OpenAI to analyze customer addresses from Google Maps and generate personalized delivery instructions, or create engaging location descriptions for real estate listings by combining map data with GPT-4's natural language capabilities.

There are numerous powerful use cases: automatically generate SEO-optimized business descriptions based on location data, create AI-powered travel guides by analyzing map information, build chatbots that provide intelligent directions and location recommendations, convert geographic coordinates into human-readable addresses with contextual information, or analyze location patterns and generate business intelligence reports. Make's visual workflow builder allows you to connect these services without coding, enabling you to trigger OpenAI's GPT models whenever new location data is received from Google Maps, or vice versa.

Not at all! Make's no-code platform makes setting up integrations between Google Maps and OpenAI accessible without any programming knowledge. You simply drag and drop modules, authenticate your accounts with a few clicks, and configure the data flow between applications using Make's intuitive interface. Make provides pre-built modules for both Google Maps and OpenAI, along with templates and documentation to guide you through the setup process. You can have your first automation running in minutes, and Make's visual editor shows you exactly how data flows between the two applications.

Make eliminates the need to write and maintain complex code, manage API authentications, handle error scenarios, or worry about server infrastructure. You get instant access to both Google Maps and OpenAI APIs through pre-built, tested modules that are automatically updated when APIs change. Make also provides built-in features like error handling, scheduling, data transformation tools, and the ability to add additional apps to your workflow as your needs grow. This means you can focus on your business logic rather than technical implementation, saving hundreds of development hours and reducing costs while maintaining enterprise-grade reliability and security.