Scale
Know whether your AI agents are working. We evaluate agents before launch and monitor them once they are live: success rate, sentiment and intent across every conversation, with dashboards and alerts for operations and leadership.
Senior people on every engagement Clients in India, the US and Europe
Scope
Understand every conversation: sentiment, success rate and customer intent.
Real-time dashboards across your AI solutions, and alerts for anomalies and opportunities.
An evaluation suite and shadow testing before go-live, run against real production test cases.
Quality assurance at intent, language and channel level, not just aggregate success rates.
Outcomes
Process
Define: agree the metrics and the intents that matter, with one definition for each.
Evaluate: test against real production cases and run in shadow before go-live.
Monitor: dashboards and alerts across voice and chat, by intent, language and channel.
Review: a weekly look at failure clusters and escalation quality, and a monthly comparison of cohorts.
Report: versioned metrics and exports for operations and leadership.
FAQ
Evaluation tests an agent against real cases before launch. Monitoring tracks it once it is live: success rate, sentiment and intent across every conversation, so you can see where it fails and which changes improve outcomes.
The Analytics platform is the dashboards, reports and exports. Evaluation and monitoring is the practice around it: deciding what to measure, testing before launch and reviewing the results every week.
Weekly reviews focus on the top failure clusters, prompt regressions and escalation quality. Monthly reviews compare cohorts and check quality by intent.
Yes. We keep event definitions consistent, so a qualified lead in voice means the same as a qualified lead in messaging, and reporting does not fragment.