Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore
Not a pilot. AWS showed how to build contract agents that extract fields AND answer portfolio-wide questions—solving what RAG alone can't.
Why it matters
Amazon Bedrock AgentCore enables multi-step contract workflows (extraction + verification + aggregation) that scale beyond single-document retrieval. The platform demonstrates how agent orchestration handles tasks RAG chat tools sidestep.
The key facts
9 to knowBedrock AgentCore + Amazon Quick for contract portfolio intelligence
Agents extract and verify contract fields across hundreds of documents
Portfolio-wide aggregation queries beyond single-contract RAG
AWS blog post includes architecture pattern, not a named customer deployment
Uses Bedrock AgentCore for agentic contract extraction and field verification
Amazon Quick handles portfolio-wide aggregate analytics and single-contract queries
Addresses documented RAG limitation: chat tools fall short on cross-contract portfolio questions
Published as AWS technical blog tutorial, not customer case study or third-party validation
Contrasts manual extraction at scale and single-document RAG chat as the baseline problems
The story so far
Earlier coverage of this storyline
- How Trane gets building insights 60x faster with Amazon Bedrock AgentCoreAWS Machine Learning Blog
- This story
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses AI agents to extract and verify contract fields, then answers aggregate and single-contract…