Score AI

Score AI audits every call, chat, email and social message, not a random sample. It scores each one against a custom scorecard and flags quality, compliance and process gaps. Supervisors get full coverage without adding reviewers, which is the main reason teams switch.

You can import your existing quality form or build a new one, then set the parameters the AI should weigh. The system decides which parameters apply based on context, and applies "NA" where a question doesn't fit. That keeps scores close to how your own auditors would judge the same ticket.

The AI reads your internal policies and knowledge base, then checks whether the resolution an agent gave matches what your documentation says. This catches wrong answers that a tone-based review would pass, and it adapts when your processes change.

Each rep gets a daily AI summary that highlights strengths and the exact interactions worth improving. Managers can log one-on-one sessions and watch whether the feedback actually moves the numbers over time. Coaching stops being a generic pep talk.

Conversations are auto-categorized into topics and sub-topics, so you can see what customers keep asking about and how sentiment shifts. New and trending concerns surface on their own, and root-cause analysis points to the process behind the complaint.

Speech analytics track pace, filler words and dead air, while smart transcription and custom tags make long recordings searchable. Supervisors jump straight to the calls that need attention rather than scrubbing through hours of audio.

AI customer personas simulate real scenarios, so new hires practice difficult calls before they go live. Teams report faster ramp-up, and the same tool helps existing agents rehearse product launches without waiting on a trainer.