Amazon Bedrock
by Amazon Web Services
AWS managed service for foundation models from Amazon and third parties; APIs return models, batch inference jobs, custom models and agents.
- Category
- Cloud & Data Platforms
- Type
- LLM provider
- Interface
- REST API
- Built with
- Connect Anything
- Credentials
- AWS access keys
02Data
What you can sync.
- Foundation models
- Batch inference jobs
- Custom models
- Provisioned throughput
- Agents
Load Amazon Bedrock foundation models into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other Amazon Bedrock data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- AWS access keys
Amazon Bedrock uses AWS access keys. You add the credentials once, when the AI asks for them, and it tells you where to create them in Amazon Web Services if you need help.
04How it works
How it works in DataMind.
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Pick Amazon Bedrock.
Open Lake, pick Amazon Bedrock in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the Amazon Bedrock API docs.
-
Answer a few questions.
The AI reads the Amazon Bedrock documentation, then asks which credentials you will use, which data to sync (for example foundation models and batch inference jobs), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
The connector agent writes a Python connector for Amazon Bedrock, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
