AI Quality Assessment Overview
High-level overview of AI-powered quality assessment (AI QA) in ConnectiveOne. This page explains what AI QA does, who it is for, and how it helps you control service quality — with a short video at the top and links to detailed instructions.
Who This Page Is For
- Supervisors and quality managers — monitor service quality, find weak points, and track improvements over time.
- Analysts — work with reports, dashboards, and exports for deeper analysis.
- Team leads — review individual conversations and coach operators based on AI assessments.
What AI QA Does
AI QA automatically analyzes dialogs and calls according to a configured checklist. Typical examples:
- Checks whether the greeting, tone, and closing of the dialog match your standards.
- Verifies whether mandatory steps were followed (verification, disclaimers, scripts).
- Highlights risk situations — rude replies, missed promises, sensitive topics.
- Assigns a score to each dialog according to your internal criteria.
You configure the checklist once, and AI QA helps apply it consistently across all dialogs — even when you have thousands of conversations per day.
This means AI QA helps you:
- apply the same quality standards to every conversation;
- quickly find conversations that need attention (low scores, risky topics);
- reduce manual sampling and scoring so the team can focus on coaching instead of spreadsheets.
How AI QA Fits Into Your Workflow
- Operators communicate with customers in chats or calls.
- AI QA analyzes selected dialogs according to your checklist.
- Supervisors and analysts review the results in reports and dashboards.
- Team leads use assessments to give feedback and plan training.
You can start with a small pilot (for one team or one line of business) and later scale AI QA to more queues and segments.
Next Steps: Detailed Guides
Use these guides to go from overview to concrete actions in the interface:
- For supervisors and analysts
- For admins and configuration
- For day-to-day work with assessments