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An Evaluator is a reusable quality-control template that defines the criteria the AI uses to audit a call transcript. You specify a set of scored criteria, assign weights, and the AI produces a structured pass/fail report for every transcription associated with this evaluator. For the full data model and criteria reference, see Evaluator.

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Your evaluators

Search, filter, and sort in real time by name, description, or evaluator ID. Sort by name or creation date (ascending/descending). Toggle between a card grid and a table layout. Each evaluator displays capability badges at a glance: To delete multiple evaluators at once, hover over any card or row to reveal its checkbox, select the items you want to remove, and click Delete selection in the action bar that appears. The table header includes a Select all checkbox for the current filtered results.
Single-item deletion is done from the detail view, not from the list.

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Creating an evaluator

Click New Evaluator to open the creation form.

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General parameters

The Name cannot be changed after creation. Choose a meaningful, descriptive name before saving.

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Evaluation context (optional)

Provides situational context so the AI understands who is being evaluated and under what circumstances. Max 1000 characters. Six preset templates are available to fill the field instantly:
Selecting a preset fills the textarea with a ready-to-edit prompt. Selecting Custom clears it.

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Evaluation criteria

Define up to 10 criteria. A N / 10 criteria used counter is shown at the top of the section. Each criterion requires:
  • Name (required, max 100 chars) — human-readable label, e.g. Corporate Greeting
  • Type — how the AI scores this criterion (see Criteria types)
  • Weight (0–100%) — contribution to the final score. Strict criteria are always 0%
  • AI Instructions (required, max 2000 chars) — natural-language description of exactly what to look for in the transcript
Weights across all non-Strict criteria must sum to exactly 100% before the evaluator can be saved. Use the Balance Weights button in the sticky bottom bar to distribute them evenly with a single click.

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Suggested Criteria panel

The right panel offers 8 pre-built criteria you can add with a single click:
The 7 non-Strict suggested criteria already sum to 100% — they form a complete, immediately usable evaluator without any manual weight adjustment.
Once a criterion has been added, its button shows a checkmark and “Already added”. It cannot be added twice.

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Quality tips

Describe concrete, verifiable actions the AI can detect in the transcript. Avoid subjective criteria.Poor: "Be friendly."Good: "Greet the client by name and thank them for the call."
Include negative examples in the AI instructions to detect violations and reduce false positives.Example: “The agent must not interrupt the client while they are speaking.”
Include expected phrases, scripts, or specific business situations the AI should recognize.Example: “The agent must mention the Premium Plus plan ($29.99/month) and at least two of its core benefits.”
Split complex criteria into simpler, focused ones. Each criterion should evaluate a single observable behavior.Poor: "Greeted AND verified identity AND offered a solution."Good: Three separate criteria — one for each action.

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Criteria types

Strict criteria are automatic disqualifiers. A single failed Strict criterion marks the entire evaluation as failed, regardless of how well all other criteria were met. Use them only for non-negotiable compliance requirements — such as identity verification or required legal disclosures.

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Viewing and editing

Click any evaluator in the list to open its detail view. Read mode shows three sections:
  • General Information — name, feedback language, description, evaluation context, creation date
  • Critical Criteria (shown only when Strict criteria exist) — red-bordered card listing each Strict criterion with its name and description
  • Evaluation Criteria — each Boolean and Scale criterion with its name, type badge, weight, and AI instructions
Click Edit to enter edit mode (amber borders and header). You can update:
  • Feedback language, description, and evaluation context
  • Criteria: edit AI instructions, type, and weight; add new criteria; remove existing ones
Name is read-only in edit mode and cannot be changed after creation.
Use the sticky Save changes bar at the bottom to confirm, or Cancel to discard all edits. The bar also shows the current weight status and the Balance Weights button. To delete an evaluator, use the trash icon in the detail view header. This cannot be undone. Deleting an evaluator does not affect transcriptions that were already processed with it.

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Cloning an evaluator

Click the Clone button (copy icon, in the detail view header alongside Edit and Delete) to duplicate an existing evaluator. You are taken directly to the creation form with all fields pre-filled:
The clone is a new draft — nothing is saved until you click Create Evaluator. Edit any field before saving, or save immediately to create an exact copy.

Evaluator

Full data model and criteria reference

Evaluator Analysis

View performance insights for this evaluator