Ask customers how satisfied they were with one specific interaction, while it is still fresh. The AI caller reads your rating scale, understands spoken answers, asks what drove the score, and sends low ratings to your team for follow-up.
Integrates with the tools you already use
One interaction, one honest rating
Use a 1-5 or 1-10 scale. The AI reads the scale aloud so the customer knows what each end means before answering.
Answers like "four", "char" or "quite satisfied" are mapped to your scale. If an answer is unclear, the AI confirms the number before moving on.
Keep separate CSAT scripts for support ticket closure, delivery, onboarding, or a store visit, each with its own wording and follow-up question.
After the rating, the AI asks one open question about what went well or what went wrong, and records the reply as text.
Ratings at or below a threshold you set are flagged to the owning team so someone can call the customer back.
Run the same CSAT script in Hindi, English, and other Indian languages so customers answer in the language they are comfortable with.
From closed ticket to a score in your dashboard
Structured data, not just a number
The numeric score on your configured scale, stored against the customer and the interaction ID.
The customer's own words on why they gave that score, transcribed for review.
The reason is grouped into themes such as wait time, staff behaviour, or product issue, so patterns show up across calls.
The agent, branch, or delivery partner tied to the interaction, if you pass it in the trigger.
Answered, completed, callback requested, or not reachable, along with retry attempts.
Results pushed back to your CRM or helpdesk via API so the score sits next to the ticket.
Trigger CSAT calls from your systems and get a score plus a reason for every interaction.