# AWS details AI contract intelligence platform using Bedrock AgentCore

Digest AI · Enterprise & Industry · published 2026-09-29T16:14:24Z

Canonical: https://digestai.news/story/aws-details-ai-contract-intelligence-platform-using-bedrock-agentcore

## Summary

AWS has published a technical guide for building a contract intelligence platform using Amazon Quick and Amazon Bedrock AgentCore. The solution addresses the limitations of standard Retrieval Augmented Generation (RAG) when handling portfolio-wide aggregation questions, such as calculating total contract value across hundreds of documents. Instead of relying solely on semantic search, the architecture uses AI agents to extract structured data from PDFs into a database, enabling precise analytics.

The system employs a dual-model verification approach to ensure accuracy. It uses Claude Sonnet 4.6 for initial data extraction and Claude Haiku 4.5 for independent verification. If the two models disagree on signature detection, Amazon Textract acts as a deterministic tiebreaker using computer vision. This design minimizes hallucinations, a common issue where models might incorrectly identify empty signature blocks as signed.

The final platform is a React web application that connects structured database records with original documents via Amazon Quick. Users can access embedded dashboards for real-time KPIs and use a natural language chat agent to ask both aggregate questions (e.g., total portfolio value) and specific document queries (e.g., payment terms). The serverless architecture allows the pipeline to process contracts in seconds and scale to handle large volumes in parallel.

## Key points

- Platform uses Claude Sonnet 4.6 for extraction and Claude Haiku 4.5 for verification to reduce errors.
- Amazon Textract resolves signature detection disagreements between the two AI models using computer vision.
- Amazon Quick connects structured data and original PDFs for both dashboard analytics and chat queries.

## Why it matters

This architecture solves a common enterprise pain point: aggregating data across large document portfolios. By combining LLMs with deterministic tools and structured databases, it offers a more reliable alternative to pure RAG for critical business data like contracts.

## Sources

1. [Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore](https://aws.amazon.com/blogs/machine-learning/building-an-ai-powered-contract-intelligence-platform-with-amazon-quick-and-amazon-bedrock-agentcore) (AWS Machine Learning Blog, 2026-09-29, primary source)

Part of the developing story: [Amazon Builds AI Operating System For Sellers](https://digestai.news/thread/amazon-expands-seller-assistant-from-chatbot-to-operating-system-for-merchants) (2 stories)

## Cite

Digest AI, "AWS details AI contract intelligence platform using Bedrock AgentCore", 29 September 2026, https://digestai.news/story/aws-details-ai-contract-intelligence-platform-using-bedrock-agentcore

---

Written by Digest AI's editorial model from the linked sources; the sources are the record. Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse
JSON: https://digestai.news/story/aws-details-ai-contract-intelligence-platform-using-bedrock-agentcore.json