Activation

Insights AI is enabled per CRM integration from the CRM Connector > Settings menu:

  1. Enable Call Data Enrichment at the general level and check your integration
  2. Enable Transcription and AI Analysis under your integration's feature toggles

Call data enrichment must be active before AI analysis can be used.

AI services incur additional charges. See our Pricing page for more information.

AI Analysis Outputs

Each processed call produces the following results, available in the call log and as mappable CRM fields:

Output CRM field(s) Description
Transcription transcription Full raw text of the conversation
Short summary summary Brief summary of the call
Detailed summary summary_detailed Longer structured summary
Sentiment label sentiments_label, sentiments_label_raw Overall sentiment: Positive, Neutral, or Negative
Sentiment score sentiments_score_average, sentiments_nets_score Numeric sentiment scores (average and net)
Sentiment evolution sentiments_evolution, sentiments_evolution_raw How sentiment changed over the call: Improving, Stable, or Deteriorating
Sentiment timeline sentiments_array Per-segment sentiment breakdown (array)
Reason for call reason_for_call AI-detected primary reason the customer called
Reason for frustration reason_for_frustration Detected source of frustration, if any
Topics topics_string, topics_array Free-form topics identified in the call
Subjects subjects_string, subjects_array Structured subjects matched to your subject tree
First Call Resolution kpi_fcr Whether the issue was resolved on first contact (boolean)
Audit grid audit_grid Full audit evaluation result (JSON)
Audit score audit_score Overall quality score from the audit grid
Recording URLs recording_urls, recording_urls_string Links to audio recordings
Transcript URLs transcript_urls, transcript_urls_string Links to transcript files

Speech KPIs

In addition to call-level AI analysis, CX-Engine computes the following speech metrics for each call:

KPI Description
agent_questions_ratio Ratio of questions asked by the agent relative to total agent utterances
customer_questions_ratio Ratio of questions asked by the customer relative to total customer utterances
agent_rephrasings_count Number of times the agent rephrased the customer's request
speech_ratio_agent Share of total speaking time attributed to the agent (0–1)
speech_ratio_customer Share of total speaking time attributed to the customer (0–1)
speech_rate_agent_wpm Agent speech rate in words per minute
speech_rate_customer_wpm Customer speech rate in words per minute
speech_rate_agent_wpr Agent speech rate in words per recording segment
speech_rate_customer_wpr Customer speech rate in words per recording segment
speech_longest_monologue_agent_duration Duration (seconds) of the agent's longest uninterrupted speech segment
speech_longest_monologue_customer_duration Duration (seconds) of the customer's longest uninterrupted speech segment
fcr First Call Resolution — whether the issue was resolved without a follow-up call (boolean)

Call Subjects

Call subjects are a hierarchical taxonomy you define to categorize calls. The AI identifies the topics discussed in each call and maps them to your configured subject tree.

Subjects are organized as a tree:

  • Each subject has a name and an optional description
  • Subjects can be nested (parent → child) to any depth
  • The full path is displayed as a hierarchical label, e.g. Support > Technical > Database

Matched subjects are stored in the subjects_array and subjects_string CRM fields.

Creating Subjects

  1. Navigate to the Call Subjects section in the Insights AI settings
  2. Click New Subject
  3. Enter a name and optional description
  4. To create a sub-subject, select an existing subject as the parent

Audit Grid

An audit grid is a scoring framework used to evaluate the quality of each call. The AI evaluates every call against your grid and produces a per-criterion score and an overall weighted quality score.

Structure

An audit grid contains:

Element Description
Label Name of the audit grid
Language Language used for AI evaluation prompts
Categories Groups of related evaluation criteria

Each category contains one or more criteria:

Field Description
Label Name of the criterion
Weighting Importance of the criterion (1–5). Higher weight means greater impact on the final score.
Instruction Prompt sent to the AI describing what to evaluate for this criterion
Checklist List of specific elements the AI looks for when forming its score
Rating scale Description of what each score from 1 to 5 means for this criterion
Exclusion conditions Conditions under which the criterion is skipped (e.g., if the situation did not arise during the call)

The overall audit score is the weighted average of all criteria scores across all categories. Excluded criteria do not affect the score.

Creating an Audit Grid

  1. Navigate to the Audit Grids section in the Insights AI settings
  2. Click New Audit Grid
  3. Enter a name and select the evaluation language
  4. Add categories and define your criteria within each category
  5. For each criterion, set a weighting, write the evaluation instruction, list the checklist items, describe the rating scale levels, and optionally add exclusion conditions

A default template grid is available to help you get started. You can duplicate it and adapt it to your needs.

Audit results are stored in the audit_grid field (full JSON with per-criterion scores and explanations) and in audit_score (overall numeric score) on each call.

Introduction Introduction