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Service Optimizer analyzes interactions with conversational agents to uncover demand that existing services are not meeting. It identifies missing or ineffective catalog services, groups repeated requests into improvement opportunities, and quantifies their potential cost and time savings. Teams can compare opportunities, validate them against the underlying user interactions, and act on the highest-value improvements, including launching Catalog Curator to create or update services.
Capabilities and value delivered
Analyzes historical conversations with HelixGPT agents to identify requests that were not successfully fulfilled.
Identifies missing catalog services and existing services that are not effectively meeting user needs.
Groups repeated requests with similar intent into consolidated improvement opportunities.
Uses supporting demand volumes and configured values to calculate potential time and cost savings for each opportunity.
Presents recommendations and opportunities by impact, with supporting evidence and direct access to Catalog Curator to create or improve services.
Surfaces repeated user needs that would otherwise remain buried across individual conversations.
Automatically finds and consolidates patterns instead of relying on teams to spot catalog gaps themselves.
Quantifies potential cost and time savings so teams can prioritize improvements by business value.
Tracks opportunities through their lifecycle and detects whether the same unmet need continues after improvements are made.