Supervisors review calls by hand
They review only a fraction of conversations — coaching whoever they reach, not whoever needs it most.
Conversational AI since 2017
Every agent sees their score across 100% of conversations, contests what's unfair, and grows on a personal plan from an AI coach. Supervisors stop reviewing calls by hand — they step in only where a live conversation is needed.
They review only a fraction of conversations — coaching whoever they reach, not whoever needs it most.
“Do better” doesn't help. They need a specific skill and an example from their own conversation.
Quality data stays a report that no one works through.
A closed loop for every agent, with no manual review: they see the score, contest what's unfair, and grow on a plan. The plan updates itself from fresh conversations.
Every one of their conversations, scored — not a sample. For each: the score, what passed, and any critical failures. Transparent from day one.
The agent disputes a specific point. The supervisor accepts it with a re-scored result or rejects it with a reason. Every change is in the audit log: who, when, and why.
The AI coach finds where the agent slips systematically and builds a personal plan: diagnosis, steps, wording — all on their own real conversations.
Every call and chat runs through the quality checklist.
A steady weakness on a criterion — not one bad day.
For each weak criterion: a diagnosis, steps to the goal, ready-made wording, a short exercise.
The agent marks progress. The supervisor steps in where a live conversation is needed.
Coach scores and coaches any customer conversation — by voice and in text.
Script, objection handling, closing the deal — on your reps' real calls.
Greeting, answer accuracy, following procedure — across every request.
Tone, empathy, first-contact resolution — in every conversation.
One task — one skill. Not abstract advice, but a breakdown on their own calls.
“Some conversations open without a greeting or introduction” — flagged as a critical failure or not.
Concrete actions in order: open with a greeting and your name, name the company, use the customer's name.
An exercise: lock in a greeting template and open with it for two weeks straight.
The agent's real calls where the gap shows: number, date, score — open in one click.
Appeal any point, with a reason. A human decides, not an algorithm.
A score changes only with justification: who, when, and why is visible.
Against a quality checklist — not breaks, mouse movement, or app activity.
Others' scores, appeals, and comments aren't accessible. The team is visible to the supervisor.
Coach runs on Sense scoring data. Three modules — one platform.
Scores 100% of conversations against checklists. The data source for Coach.
The agent room, appeals, AI growth plans — on top of that scoring.
The same data in dashboards: teams, criteria, trends, comparisons.
A composite profile of the team where Coach delivers the most.
We set up the data source: telephony and chat channels. If Lia Sense is already connected, this step drops. From you: channel access and a test sample of conversations.
We build scoring for each channel: greeting, identifying the need, answer accuracy, closing. We agree on weights and the passing score.
Agents get “My conversations”, appeals, and growth plans. Supervisors get “Team coaching”. One hour of training per role, ready-made onboarding material.
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