Customer Experience Monitoring for AI Products
Product managers, support leaders, customer success teams
Traditional observability can show that infrastructure is healthy while the AI experience is getting worse. Users may abandon tasks because answers are less useful, slower, more expensive, or harder to complete.
Customer experience tied to AI behavior
AnoSys connects user behavior, engagement, quality, latency, errors, evals, cost, and business KPIs so product and support teams can see whether the AI experience is improving or degrading.
Connect journey data to traces, evals, latency, cost, and outcomes so product teams know what changed.
Connect
Bring user events, application telemetry, AI traces, evals, latency, and business KPIs together.
Segment
Compare experience by customer, cohort, workflow, model, release, or process.
Explain
Find whether quality, latency, cost, tool failures, or data issues changed the outcome.
Improve
Route product, support, and engineering actions with evidence from the full journey.
What supports it
How to start
Why teams buy it
- Catch quiet customer-experience degradation before it shows up in churn or tickets.
- Show product teams which AI behaviors improve or hurt outcomes.
- Give support and success teams context behind escalations and customer pain.
Is this web analytics?
AnoSys can ingest user behavior signals, but the value comes from connecting them to AI traces, evals, latency, cost, and business outcomes.
Can support teams use AnoSys?
Yes. Support teams can use dashboards, AI Assistant, and workflow evidence to understand why a customer was affected and what changed.