How to connect Google Cloud Speech-To-Text and MongoDB
Create a New Scenario to Connect Google Cloud Speech-To-Text and MongoDB
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud Speech-To-Text, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Speech-To-Text or MongoDB will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or MongoDB, and select the appropriate trigger to start the scenario.

Add the Google Cloud Speech-To-Text Node
Select the Google Cloud Speech-To-Text node from the app selection panel on the right.

Google Cloud Speech-To-Text
Configure the Google Cloud Speech-To-Text
Click on the Google Cloud Speech-To-Text node to configure it. You can modify the Google Cloud Speech-To-Text URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the MongoDB Node
Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select MongoDB from the list of available apps, and choose the action you need from the list of nodes within MongoDB.

Google Cloud Speech-To-Text
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MongoDB

Authenticate MongoDB
Now, click the MongoDB node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MongoDB settings. Authentication allows you to use MongoDB through Latenode.
Configure the Google Cloud Speech-To-Text and MongoDB Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud Speech-To-Text and MongoDB Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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AI Anthropic Claude 3
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MongoDB
Trigger on Webhook
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Google Cloud Speech-To-Text
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud Speech-To-Text, MongoDB, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud Speech-To-Text and MongoDB integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and MongoDB (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud Speech-To-Text and MongoDB
Google Cloud Speech-To-Text + MongoDB + Slack: Transcribes audio files stored in Google Cloud Storage using Speech-To-Text, inserts the transcribed text into a MongoDB database, and then sends a notification with the transcription to a designated Slack channel for the support team.
MongoDB + Google Cloud Speech-To-Text + OpenAI ChatGPT: Retrieves call recordings metadata from MongoDB, uses Google Cloud Speech-To-Text to transcribe the audio, and then analyzes the transcribed text with OpenAI ChatGPT to determine sentiment and generate a summary.
Google Cloud Speech-To-Text and MongoDB integration alternatives
About Google Cloud Speech-To-Text
Automate audio transcription using Google Cloud Speech-To-Text within Latenode. Convert audio files to text and use the results to populate databases, trigger alerts, or analyze customer feedback. Latenode provides visual tools to manage the flow, plus code options for custom parsing or filtering. Scale voice workflows without complex coding.
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About MongoDB
Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.
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FAQ Google Cloud Speech-To-Text and MongoDB
How can I connect my Google Cloud Speech-To-Text account to MongoDB using Latenode?
To connect your Google Cloud Speech-To-Text account to MongoDB on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Speech-To-Text and click on "Connect".
- Authenticate your Google Cloud Speech-To-Text and MongoDB accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I archive transcribed meeting notes to MongoDB?
Yes, you can! Latenode simplifies this process, automating the transfer of transcript data for organized storage and easy analysis. Benefit from no-code blocks and scalable infrastructure.
What types of tasks can I perform by integrating Google Cloud Speech-To-Text with MongoDB?
Integrating Google Cloud Speech-To-Text with MongoDB allows you to perform various tasks, including:
- Storing call center transcriptions for sentiment analysis.
- Archiving voice assistant logs for future reference.
- Creating a searchable database of podcast transcripts.
- Analyzing customer feedback from voice surveys.
- Building a knowledge base from transcribed audio content.
How secure is Google Cloud Speech-To-Text data transfer via Latenode?
Latenode employs secure connections and data encryption, ensuring your Google Cloud Speech-To-Text data is safely transferred and stored in MongoDB.
Are there any limitations to the Google Cloud Speech-To-Text and MongoDB integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may require longer processing times.
- Transcription accuracy depends on audio quality.
- Complex workflows may require JavaScript coding.