Knowledge gap report

An AI support agent grounded in your knowledge base fails in a specific, observable way when the content is missing: retrieval returns nothing relevant, confidence is low, or the customer rejects the answer and escalates. Logging those events and clustering them by topic produces a knowledge gap report. Each cluster shows the question as customers phrase it, how often it occurs, how it was resolved by humans when escalated, and an estimate of the tickets that would be avoided if an article existed.

This turns the AI into an instrument for improving the help centre rather than just consuming it. Before AI, content teams guessed what to write from ticket tags; the gap report shows exactly which questions are being asked in customers' own words and which existing articles are being retrieved but not solving the problem (a signal of outdated or unclear content, not missing content).

It is not a hallucination log or a general quality dashboard. It is narrowly about content coverage, and its output is a prioritised writing queue for the documentation or support-content owner.

• Support manager: it is the most direct lever on auto-resolution rate; each closed gap converts escalations into resolutions.
• Product manager: recurring gaps often reveal confusing features or missing product capabilities, not just missing articles.
• Founder / CEO: it makes the AI's improvement over time visible and attributable rather than mysterious.
• Operations head: it gives the content team a ranked backlog based on real demand instead of intuition.

Grounded AI agents are only as good as the content behind them, and most help centres were written for a different era of search and never audited against real questions. The knowledge gap report exists to close that loop systematically: the agent surfaces what customers actually ask, the content team fills the gaps, and resolution rises. The trade-off is that it requires ownership; a report no one acts on is just another dashboard. Eazyware delivers it as part of Care Plans for support agents, with a monthly review where gaps are assigned and the effect on resolution is tracked.

• SaaS: discovering that integration-setup questions for a new connector dominate escalations before any article exists.
• FinTech: identifying repeated questions about a new fee or KYC re-verification step after a regulatory change.
• E-commerce: surfacing size-guide and return-window questions for a newly launched category.
• EdTech: finding that students ask about a scholarship deadline in five phrasings the FAQ does not match.
• Healthcare: revealing insurance-network and pre-authorisation questions the hospital website never addressed.

Tool / technologyA reporting artefact generated from the agent's retrieval and escalation logs. Eazyware includes it in Customer Service Agents deployments and reviews it monthly under Care Plans so that content fixes are tracked against resolution gains.

Eazyware service that covers it: AI Customer Service Agents. Starting prices are on the pricing page.