Genesys Cloud – AI virtual assistant on Resource Center

In a future release, Genesys Cloud will introduce an AI-powered virtual assistant on the new Resource Center (help.genesys.cloud) to make it easier and faster for users to find the help they need. This assistant will offer guided, conversational support backed by Agentic Virtual Agent, Knowledge Workbench V2, and AI Guides.

Previously, users relied solely on traditional search and manual navigation through growing documentation. The new assistant reduces the time users spend locating relevant information by delivering concise, contextual, source-linked answers directly within their workflow. It also helps internal teams understand where documentation can be improved by surfacing analytics on engagement and gaps.

What’s changing — overview

• Conversational Q&A over documentation — Users can ask questions in natural language or follow scripted menus to receive precise answers grounded in Resource Center content.
• Smart summarization — The assistant provides short, focused answers with optional “dive deeper” expansions to avoid overwhelming users while still offering depth when needed.
• Multimedia surfacing — Responses can include articles, videos, announcements, and deprecations to present the most helpful format for each question.
• Analytics and insights — Internal teams gain visibility into user queries, satisfaction, and no-answer cases, allowing continuous improvement of documentation and support experiences.

Why this is a good improvement

• Faster access to help
  Users no longer need to switch contexts or navigate multiple articles. The assistant retrieves and synthesizes content for them, reducing friction and time-to-answer.
• Better discoverability
  As documentation grows, finding the right resource becomes harder. Conversational retrieval helps users reach the correct information without guessing which article to open.
• Higher support deflection
  Clear, accurate answers reduce reliance on Product Support for common questions, improving efficiency and resolution time.
• Actionable insights for internal teams
  Analytics highlight what users search for, where content is missing, and how effective existing articles are. This supports more targeted documentation updates.

Who benefits

• End users and customers seeking quick, contextual help
• Prospects who want to explore capabilities in a guided way
• Internal teams – support, documentation, product management (gaining insights to refine help experiences)

How it works — high-level approach

• RAG retrieval across indexed Resource Center content with citations
• Orchestration pipeline for intent detection, retrieval, answer synthesis, and safe fallback responses
• Lightweight UI embedded directly in the Resource Center with expand/collapse behavior
• Safety controls that ensure responses stay within supported actions and always cite their sources
• Observability via structured logs, redaction, and analytics instrumentation