Amazon Quick: a conversational AI agent for combining structured and unstructured data
AWS showed how to combine structured data (databases, metrics) and unstructured content (documents) in Amazon Quick into a single conversational agent that itself determines the source of the answer and adds citations.
AWS described in a guide on the AWS Machine Learning Blog how to combine structured data (metrics, sales figures, KPIs) with unstructured content (documents, PDFs, reports) in Amazon Quick into a single conversational interface. The solution is built on three layers: the data layer stores unstructured content in Amazon S3 and indexes it via a knowledge base, while structured data is uploaded as an enriched dataset with semantic descriptions that help the agent translate queries into SQL. The workspace layer (Space) connects both sources into a shared context, and the agent layer then determines whether a query should be routed to the knowledge base, the dataset, or both at once.
According to AWS, the agent returns a combined answer with source citations and includes built-in safety features, such as content safety screening. Responses also respect the permissions of the user who submitted the query. The guide describes specific steps: creating an S3 integration, setting up a knowledge base, creating and enriching a dataset, and then building a chat agent linked to the Space.
According to AWS, creating datasets in Amazon Quick requires an Enterprise subscription. The source article is a technical walkthrough and its text was only partially available — details on further steps and configuration can be found in the source article.
Why it matters
For companies whose data is split between databases and document storage, there is no longer a need to switch between analytical and search tools and manually merge results. Source citations and respecting user permissions make it easier to verify answers and control access to sensitive data. However, the requirement for an Enterprise subscription to create datasets is a limiting factor that companies must take into account when planning.
Two audiences, two different impacts
What this means
For individuals
A user working with Amazon Quick can, following AWS's guide, set up an environment where queries are run simultaneously over documents and tabular data, without having to manually switch between tools.
For a business
In Amazon Quick, companies can combine querying across databases and documents into a single conversational interface, eliminating the need to switch between tools and manually match results. However, creating datasets requires an Enterprise subscription.
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Event sources
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