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Backendless
Google Gemini AI

Connect Backendless and Google Gemini AI

Explore ready-made Backendless and Google Gemini AI templates and start automating in minutes.

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Create a custom workflow

Integrate Backendless with Google Gemini AI and automate the work that moves between them — no code required.

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.

Backendless
Trigger: Watch a Created Object
Google Gemini AI
Action: Select an action
1. Select a trigger

  • Triggers when a new object is created in chosen data table.

  • Triggers when a registered user logs into your Backendless application.

  • Triggers when a logged in user logs out.

  • Triggers when a new file is uploaded.

  • Triggers when a new user is registered in your Backendless application.

  • Triggers when an object is removed from the data table.

  • Triggers when a user is removed.

  • Triggers when an object is updated in the selected table.

  • Triggers when a user data is updated.

  • Triggers when a file or directory is deleted in your Backendless application.

2. Select an action

  • Creates a new file search store.

  • Deletes a file from a selected files search store.

  • Deletes a file search store.

  • Extracts structured data from text or files.

  • Generates a response for the provided input.

  • Generates a video using the general purpose Gemini model family.

  • Generates a video using the Veo models.

  • Generates an image using Gemini's image generation capabilities.

  • Generates an image using the imagen models.

  • Generate vector representations (embeddings) for the text or file you provide.

  • Generate high-quality, stereo audio from text prompts or from images.

  • Generates an audio file based on text input and settings.

  • Returns detailed information about a file in a file search store.

  • Retrieves details about a file search store.

  • Retrieves the full details of a single interaction (e.g. from a deep research agent).

  • Performs an arbitrary authorized API call.

  • Runs a deep research agent by Gemini.

  • Generates text responses from prompts without requiring an account or connection.

  • Uploads a file so it can be used in the completions or in file search stores.

Select a trigger and an action

Create workflow (opens in a new tab)

Triggers and actions

Explore what you can automate between Backendless and Google Gemini AI.

Create a file search store
Creates a new file search store.
Action
Delete a file in a file search store
Deletes a file from a selected files search store.
Action
Delete a file search store
Deletes a file search store.
Action
Delete an Object from the Database
Deletes an object from a specified table by ObjectId.
Action
Extract structured data
Extracts structured data from text or files.
Action
Find Objects in the Database
Runs a query to the database to retrieve objects.
Search
Generate a response
Generates a response for the provided input.
Action
Generate a video
Generates a video using the general purpose Gemini model family.
Action
Generate a video (Veo) (deprecated)
Generates a video using the Veo models.
Action
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FAQs

Everything you need to know about Make. Can't find the answer you're looking for? Please chat to our team.

Start by registering for Make. As a new Make user, you’ll automatically be assigned a free account. Once your account is set up, you can start creating your first scenarios. We recommend starting with our step-by-step video tutorial.

A scenario represents a workflow or a project of your own creation, and it is made up of a series of modules that automate apps and services. Creating a scenario allows you to transfer and transform data between apps and services via these modules to automate anything and improve the way you work.

Modules are the main building blocks of automation in Make. Modules represent actions that Make performs with an app, like creating, updating, or deleting data.

Mapping links the modules in your scenario. When you map an item, you connect the data retrieved by one module to another module to perform the desired action. For example, you can map email addresses and subject lines to create a spreadsheet using this data.