Knowledge Orchestration

Turn real customer conversations into the knowledge your AI needs.

Build knowledge around real questions

eGain Knowledge Orchestration is the conversation analysis capability in the eGain AI Knowledge Hub. It extracts the questions customers and employees ask in calls, chats, messages, and searches, ranks them by volume, value, and complexity, and shows whether your knowledge base answers each one. Knowledge authors get a ranked list of what to write, update, or leave alone, based on real demand instead of assumptions.

Knowledge Orchestration is one half of eGain Knowledge Automation. It covers what people ask, while Knowledge Intelligence covers what your knowledge base contains.

Most knowledge bases are built on guesses about what people will ask.

Without evidence from real conversations, teams write content for the questions they expect and miss the ones customers bring.

Content misses the questions customers really ask

Most knowledge bases are planned around what a team assumes customers will want to know. Once the content is live, there’s no easy way to check those assumptions, and popular questions can go unanswered while effort goes into content few people need.

The reason for an inquiry is buried in the conversation

Customers rarely ask a question in a direct manner. The question behind a call or chat can sit in the middle of a long exchange, so the reason for the contact often goes unrecorded or gets logged under the wrong category.

New fixes don’t reach the knowledge base

When an agent resolves a new issue, the answer usually stays in a transcript or in that agent’s memory. The next customer with the same question starts from scratch, and so does the next agent.

Assess your Content against Real Customer Demand

Knowledge Orchestration assesses the content and conversations you’ve captured from scattered sources through kForge content migration services, WYCA conversation analysis, or eGain AI Knowledge Connectors. It looks at what customers and employees ask across search, calls, chat, and messaging, and shows which questions your knowledge answers well and which ones it misses. Teams get a clear picture of where their content stands before they decide what to write or fix.

Prioritize by Volume, Value, and Complexity

Each question is ranked on three factors, and together they give teams one ranked list of the questions that will deliver the most benefit once they are answered well.

  • Volume: How often the question comes up
  • Value: What it costs to keep answering the question manually
  • Complexity: How hard it would be to automate, including any compliance requirements

See How Well Your Knowledge Answers Each Question

Each extracted question is matched to the closest topic already in your knowledge base and scored on whether existing content answers it fully, partially, or not at all. Authors can see which articles are in good shape, which need a touch-up, and which questions need new content, without creating duplicates along the way.

Draft New Articles from Past Resolutions

When no article answers a question, Knowledge Orchestration looks for past conversations where the question was resolved and drafts a new article from that resolution. Knowledge that only experienced agents know becomes content everyone can use.

Recommend the Right AI Response Method

Based on a question’s complexity and compliance needs, Knowledge Orchestration suggests how AI should answer it. Simple questions can get a quick AI-generated answer. Questions with strict compliance requirements can get a certified response delivered word for word. Complex questions can use case-based reasoning that walks through similar past situations.

Part of eGain Knowledge Automation

Knowledge Orchestration focuses on demand, telling you what people ask and how well your content answers questions. Knowledge Intelligence focuses on quality, auditing published content for consistency, compliance, and correctness.

Knowledge Automation connects the two in one continuous loop, so gaps between questions and content are caught and fixed without manual reconciliation.

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