Xect AI's transcript analyst classifies contact reasons and estimates sentiment patterns across available call and chat summaries shortly after each interaction ends. It gives supervisors prioritized interactions and recurring service drivers to support quality review and operational improvement.
Care center staff used to track intents by hand and e-mail the report. Sampling hid the intents that mattered and emotion surfaced days later in survey verbatims. Xect AI classifies every summary as it arrives, scores the emotion, and publishes the report on schedule.
Every call and chat summary lands as an event with queue, agent and customer attached.
Intent and sub-intent come from the knowledge-graph taxonomy, so "my promo ended" and "bill went up" land in the same bucket.
Dominant sentiment and the emotional arc — steady, evolving, declining — are estimated per transcript from language patterns; declines above threshold flag for review.
Call Patterns & Drivers by center and the agent-activity view refresh on schedule; supervisors get the flagged list, not the haystack.
Each agent owns one step in the transcript-to-report path above and hands off cleanly to the next.
Names the reason for every contact.
Reads each summary and assigns intent and sub-intent from the industry taxonomy, so the same underlying reason is grouped consistently across agents, queues and phrasing.
Identifies language patterns associated with customer sentiment.
Analyzes language patterns in each transcript summary to estimate sentiment and how it shifts across the conversation, then flags transcripts where the estimated sentiment declines enough to warrant a look.
Publishes the report the team used to write.
Rolls every classified transcript into the Call Patterns & Drivers report and the agent-activity view, and delivers both on a schedule with no one compiling a spreadsheet.
Every call and chat summary routed to Xect AI as an event gets classified, not just the fraction a QA team could review by hand.
Care, Collections, Dispatch, Field, SMB and Technical Service each see their own three drivers.
The cumulative call-pattern report and the hourly activity view publish on schedule, freeing analysts to focus on taxonomy, corrections and interpretation.
The Emotion Agent flags any transcript whose estimated sentiment drops past the review threshold, so supervisors see it while a save is still possible.
The report the team used to build by hand now arrives before the shift ends.
When "service performance" overtakes "billing" as the top Technical Service intent by 2 PM, the network team hears about it the same afternoon.
See the industry pageWhen claim-status calls spike after a storm, the driver report shows which region and which adjuster queue.
Talk to us about insuranceWhen appointment-reschedule intents climb, patient access sees it before the no-show rate does.
Talk to us about healthcareWhen "high bill" intents rise with the first cold week, the outreach campaign starts that day.
Talk to us about utilitiesWhen "where is my order" dominates a carrier's region, the ops team knows which carrier.
Talk to us about retailOwns the quality of the queue's conversations, and needs the transcripts most likely to need a save ranked and ready, not buried in a full-queue review.
Owns the intent report and the quality scorecards, and needs the report to publish on its own so the hours once spent tallying go to acting on what it shows.
Owns the customer care organization's results, and needs the true drivers behind every queue's volume without waiting on a sample or a quarterly review.
Owns the chatbot and self-service backlog, and needs the actual reasons customers call, sub-intent included, to prioritize deflection instead of guessing.
Book a 30-minute demo and watch a week of your transcripts become intents, emotions and a published report.