eGain Introduces AI KnowledgeOps to Power Trustworthy AI From Living Knowledge
Key Highlights
- ➤eGain introduced AI KnowledgeOps, a framework for maintaining accurate enterprise knowledge for AI.
- ➤eGain launched four capabilities: WYCA, Knowledge Graphs, Genie, and kForge.
- ➤WYCA analyzes customer conversations inside company firewalls to identify high-priority knowledge needs.
- ➤eGain Knowledge Graphs connect business topics with trusted articles for more complete AI answers.
- ➤eGain kForge consolidates and transforms content, with source tracing and expert review for high-risk changes.
Expert Statements
Ashu Roy, CEO of eGain
“The first thing every executive wants to know before putting AI in front of customers is whether it will get the answer right and take the right action, and both come down to the knowledge behind it”
Ashu Roy, CEO of eGain
“AI KnowledgeOps gives companies a repeatable process to make sure it does, even as their business keeps changing.”
Ashu Roy, CEO of eGain
“We've spent more than 25 years helping enterprises manage knowledge, and the organizations seeing real results from AI are the ones that treat knowledge as an ongoing practice.”
Ashu Roy, CEO of eGain
“The capabilities we're introducing today make that practice faster and easier to maintain, so teams can bring their content together, see what customers actually need, and keep every answer and action current.”
SUNNYVALE, Calif., Oct. 13, 2026 (GLOBE NEWSWIRE) -- eGain (NASDAQ: EGAN) today introduced AI KnowledgeOps, an industry framework for keeping enterprise knowledge accurate and ready for AI as a business and its industry keep changing. It gives organizations an ongoing way to make sure the answers and actions AI delivers are consistent and correct, so companies can rely on AI across more of their customer and employee interactions. Alongside the framework, eGain introduced four new capabilities that make it faster and easier for teams to run AI KnowledgeOps every day.
AI makes it easy to produce an answer that sounds right whether or not it is. When an AI agent gets an answer or an action wrong, the business pays for it in a poor customer experience, a higher cost to fix, and compliance exposure in regulated industries. AI models can only be as reliable as the knowledge content they draw from.
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