---
title: "Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore"
slug: "vertragsanalyse-mit-amazon-quick-und-bedrock-agentcore-ai-plattform-fuer-vertragsdaten"
date: 2026-09-29
category: tech-pub
tags: [agents, amazon]
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/vertragsanalyse-mit-amazon-quick-und-bedrock-agentcore-ai-plattform-fuer-vertragsdaten
---

# Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore

**Published**: 2026-09-29 | **Category**: tech-pub | **Sources**: 1

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## TL;DR

Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions.

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## Summary

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 questions through Amazon Quick analytics.

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## Why it matters

Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions.

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## Key Points

- 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 questions through Amazon Quick analytics.

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## Nauti's Take

Agents that extract and verify contract fields are a real opportunity to answer portfolio questions where simple RAG chats fail. The risk lies in extraction errors: a misread termination date costs money. Teams with many contracts should build in spot checks and human review.

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## FAQ

**Q:** What is Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore about?

**A:** Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions.

**Q:** Why does it matter?

**A:** Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions.

**Q:** What are the key takeaways?

**A:** 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 questions through Amazon Quick analytics.

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## Related Topics

- [agents](https://news.ainauten.com/en/tag/agents)
- [amazon](https://news.ainauten.com/en/tag/amazon)

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## Sources

- [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

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## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

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*Last Updated: 2026-09-30*