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This guide covers how to configure an Amazon Bedrock credential in Validio to access AI foundation models for generating SQL queries in custom validators and filters.
The Amazon Bedrock credential configuration form, showing name, model, AWS region, and API key fields

Configuration for Amazon Bedrock credential

Amazon Bedrock provides access to AI language models from AI companies (like Anthropic, Meta, Mistral, and Amazon). By adding an LLM credential for Amazon Bedrock to Validio, you can leverage the capabilities of selected models to generate SQL queries for custom validation and filtering.

Prerequisites

Before setting up your Amazon Bedrock credential, ensure you have:
  • Enabled the Allow LLM credentials setting in your Validio Workspace (requires Global settings:WRITE)
  • Appropriate permissions to create credentials in your Validio namespace (requires credentials:WRITE)
  • An active AWS account with an IAM identity that has permissions to use the Amazon Bedrock console.
  • An Amazon Bedrock API key (you can generate one from the Amazon Bedrock console). Refer to Generate an Amazon Bedrock API key in AWS documentation.

Add an Amazon Bedrock credential

Because each Amazon Bedrock credential is tied to one language model, you should add one credential for each model you want to use in Validio.
To add an AWS Bedrock credential,
  1. Navigate to Credentials and click + New credential.
  2. Namespace: Select the namespace where the resources will be created.
  3. Credential Type: Select AWS Bedrock from the dropdown.
  4. Configuration: Complete the required parameters.
  5. (Optional) Click Test credential to validate that Validio can successfully connect to Amazon Bedrock using your configuration. If the test fails, verify your API key is correct.
  6. Click Create credential to save your configuration.

Next steps

With your Amazon Bedrock credential configured, you can leverage AI models across various Validio features: