01
Your service standard as the benchmark
Register each service channel and its expected flow, step by step, with the planned time for each one. This standard, defined by your company, drives every evaluation.
02
AI agents acting as customers
Agents talk to your channels as customers, following the scenarios you define. Tests draw on a request package and can run on a recurring basis, keeping pace with your operations.
03
Evidence-based evaluation, no made-up scores
Language models read each conversation, identify the flow steps and evaluate every criterion. When the conversation has no evidence, the result is recorded as "not observed" or "not performed", never as an estimated score.
04
The actual time of every step
Each step's duration is measured in the conversation itself and compared with the planned time. You find out where service slows down and which steps are being skipped.
05
Comparable metrics
Conversations become comparable indicators by channel, step and period, always measured against your registered parameters. Service improvement becomes visible over time.
06
Results where your team already works
Follow everything in the dashboard or send results to BI, CRM and alerting tools through the public API and webhooks, with no manual exports.
07
Ethical, secure and under your control
No test runs without a signed authorization from the company and an available package balance. The agent never uses real personal data and never confirms purchases or bookings. Each company's data is fully isolated, and package usage is debited precisely, with no double charges. AWS infrastructure in Brazil (São Paulo), with Anthropic's Claude via Amazon Bedrock.
Mystery shopping · AI · SaaS