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QA for every support call, chat and email.

Support leads usually score a handful of tickets per agent. Assay checks every conversation for identity checks, complaints, refund promises and how the customer was left, and sends the unclear ones to your QA team.

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1,284

Checked today

7

Need a person

96%

Agreed with reviewers

Customer support conversationChecking…3 checks in 140 ms
  1. 14

    Agent

    Can you confirm the postcode on the account for me?

    Identity confirmedRecorded automatically

  2. 15

    Customer

    This is the third time I’ve had to chase this.

    Complaint raisedSent to your review queue

  3. 16

    Agent

    I’ll refund the full £180 today.

    Refund approved firstFailed on this line

Rules customer support teams start with

Written in plain English. Use them as they are, reword them, or paste in your own scorecard.

  1. Agent confirms the customer’s identity before discussing the account.
  2. A complaint is recognised and logged when the customer expresses dissatisfaction.
  3. Refunds over £50 are only promised after supervisor approval.
  4. Agent summarises next steps before ending the call.

Every conversation checked, not a sample

Reviewing by hand

2 of 100 conversations read. The other 98 are never looked at.

With Assay

100 of 100 checked. 2 failed a check, 5 went to a person, the rest were recorded.

How it works

  1. Calls, chats and emails arrive

    Imported from your helpdesk or bucket, uploaded, or sent through the API.

  2. Checked against your scorecard

    Each check is answered yes, no or not sure.

  3. Clear results are recorded

    With the line in the transcript that decided them.

  4. Uncertain ones go to a person

    They land in your review queue.

Other teams using Assay

SalesCollectionsInsurance and lendingRecruitmentAI agents

Try it on your own calls

Tell us about your team. We’ll reply within two working days to set up a trial with 50 of your transcripts and your current scorecard.

  • No card or contract for the trial
  • Your conversations are never used to train models
  • We go through the results with you