Co-authored with Ben Snively, this AWS blog post walks through how to index and add Confluence data sources to Amazon Kendra for ML-powered intelligent search.

Amazon Kendra is an intelligent search service powered by machine learning. Unlike traditional keyword-based search, Kendra uses natural language understanding to return precise answers from unstructured data across an organization. The Confluence Server connector allows you to index your Confluence spaces, pages, and blogs directly into Kendra, making all that institutional knowledge searchable through natural language queries.

The post covers the end-to-end setup: configuring the Confluence Server connector, setting up the necessary IAM roles and VPC networking, defining the index and data source, and running the first sync to crawl and index your Confluence content. Once configured, users can ask questions in plain English and Kendra returns the most relevant answers from across their Confluence knowledge base.

Read the full post on AWS