Get in touch

Most organizations have knowledge drift. The website says one thing, the knowledge base says another, and agents improvise. CQI detects what customers actually ask, finds gaps and conflicts, and drives targeted fixes so answers stay accurate across sources.

Dashboards tell you what happened. CQI helps you fix the cause, the knowledge gaps, and keep improving over time. It does not replace your chatbot. It improves what the chatbot and agents rely on, accurate and consistent knowledge.

You will see early insights quickly, such as top contact reasons and recurring question themes. Measurable impact follows once fixes are implemented and rolled out across channels, typically within weeks to a few months, depending on volume and governance speed.

Service and CX teams, especially Service Leads, Knowledge Managers and Authors, Bot Owners, and SMEs, who want fewer repeat contacts and consistent answers across channels.

CQI monitors incoming questions, groups them into clear contact reasons, maps them to the knowledge sources used to answer them, and flags what is missing, outdated, or inconsistent, then proposes concrete improvements.

Human in the loop by design. CQI suggests changes with supporting evidence, but your team reviews, edits, and approves before anything is published, so governance stays with you.

Typically voice transcripts, chat, email, and ticket notes, anywhere customers ask questions and agents respond. If it is text, or can be transcribed to text, it can usually be analyzed.

Common sources include knowledge bases, intranet and SharePoint like repositories, website help centers, and chatbot knowledge stores. The goal is to connect to your existing knowledge sources, so you can improve what you already have without replacing your current tools.

CQI is designed for sensitive customer service environments with access control, least privilege, and enterprise security expectations such as secure storage, auditability, and separation of environments. For pilots, you can also start with anonymized or redacted data.

A sample of interaction data or transcripts, read access to key knowledge sources, and two to three stakeholders, typically a service lead plus a knowledge owner or content editor, to validate findings and approve improvements.