Connect Cradl AI and Google Cloud Bigtable to Build Intelligent Automations
Choose a Trigger
When this happens...
New Document
New Dataset
Choose an Action
Automatically do this!
- Request a new Action for Google Cloud Bigtable
Enable Integrations or automations with these events of Cradl AI and Google Cloud Bigtable
Enable Integrations or automations with these events of Cradl AI and Google Cloud Bigtable
Triggers
New Document
Triggers when a new document is created.
New Dataset
Triggers when a new dataset is created.
Actions
List Documents
Get all existing documents.
Create Dataset
Create a new dataset.
Create Document
Create a new document.
List users
Get all existing users.
List Agent
List all Agent in Cradl AI.
Create agent
Create a new agent.
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Frequently Asked Questions
To start, connect both your Cradl AI and Google Cloud Bigtable accounts to viaSocket. Once connected, you can set up a workflow where an event in Cradl AI triggers actions in Google Cloud Bigtable (or vice versa).
Absolutely. You can customize how Cradl AI data is recorded in Google Cloud Bigtable. This includes choosing which data fields go into which fields of Google Cloud Bigtable, setting up custom formats, and filtering out unwanted information.
The data sync between Cradl AI and Google Cloud Bigtable typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Cradl AI and Google Cloud Bigtable. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Cradl AI
Cradl AI is a no-code tool for automating document workflows using customized AI - fully automated or with human-in-the-loop validation.
Learn MoreAbout Google Cloud Bigtable
Google Cloud Bigtable is a fully managed, scalable NoSQL database service designed for large analytical and operational workloads. It is ideal for applications that require high throughput and low latency, such as IoT, user analytics, and financial data analysis.
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