{
  "id": 2012776,
  "title": "KnowledgeForge: mining gold from the ITSM ticket graveyard",
  "url": "https://urgent.news/2026/08/19/knowledgeforge-mining-gold-from-the-itsm-ticket-graveyard",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-19T20:36:50.000Z",
  "source": {
    "name": "AWS Machine Learning",
    "slug": "aws-machine-learning",
    "url": "https://aws.amazon.com/blogs/machine-learning/knowledgeforge-mining-gold-from-the-itsm-ticket-graveyard/"
  },
  "original_language": "en",
  "account": "The KnowledgeForge solution addresses the issue of valuable but unused knowledge locked away in resolved IT Service Management (ITSM) tickets. When IT support teams resolve tickets, they often contain useful information, such as symptoms, root causes, and fixes applied by engineers. However, this knowledge remains hidden inside ticket history, making it inaccessible for future engineers facing similar problems. At the same time, the knowledge base itself faces challenges, such as duplicate articles, outdated content, and varying quality. To tackle these problems, KnowledgeForge works on both ends of the knowledge gap.\n\nThe system mines resolved incident tickets for new articles while simultaneously improving the existing knowledge base by sorting articles by type, removing duplicates, assessing their quality, and refining weak content. A knowledge manager reviews and approves the final results, ensuring that only high-quality content goes live. This process helps create a more effective and efficient knowledge base.\n\nThe core components powering KnowledgeForge include Amazon Bedrock for generation and content improvement, Amazon S3 Vectors for duplicate detection, and AWS Step Functions for workflow orchestration. By combining these AWS services, the solution provides a scalable and efficient way to process large amounts of document data using generative AI. If you are building a large-scale document-processing pipeline with generative AI, you can leverage these same patterns to create a more efficient and valuable knowledge base for your organization.",
  "summary": "KnowledgeForge mines resolved ITSM incident tickets into new knowledge base articles and automatically curates the existing library by deduplicating, quality-scoring, and improving content, using Amazon Bedrock, Amazon S3 Vectors, and AWS Step Functions in a multi-tenant, closed-loop pipeline.",
  "key_points": [
    "KnowledgeForge extracts valuable knowledge from resolved ITSM tickets.",
    "System improves knowledge base by sorting, removing duplicates, and refining content.",
    "AWS services power scalable, efficient processing of document data."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}