See it on your own interactions
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- GDPR and LGPD compliant
- 99% agreement with human evaluators
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AI quality monitoring
Your quality program audits 4% of your operation and hopes it is representative
Sampling is not a methodology. It is what fits in the hours your team has. BRIGGS scores 100% of your interactions against your own scorecard, with 99% agreement with the evaluators you already trust.
100%
of interactions audited
calls, chat, WhatsApp, video
99%
agreement with human evaluators
measured against calibrated supervisors
11 → 4
analysts on one customer
coverage went from 5% to 99%
What changes when coverage stops being the constraint
Every interaction, not a sample
Sampling was never a methodology choice. It was a headcount limit. We score every call, chat and message, so the pattern you act on comes from the whole operation rather than from the forty conversations someone had time to open.
Your scorecard, your criteria
The model is calibrated against the judgment of your own evaluators until it agrees with them. Not a generic sentiment score: the criteria your supervisors already defend in a review meeting.
Your analysts move up the stack
When coverage stops depending on listening hours, the quality team stops listening and starts calibrating criteria, reviewing edge cases and coaching with the exact moment in hand.
The math nobody runs before hiring
A quality analyst in the US costs around $93,000 a year fully loaded, and audits roughly 415 interactions a month. In a 40-seat operation that is 4% coverage. Reaching 99% by hiring takes 97 analysts and $751,750 a month.