Errors, retries, tool failures, and slow handoffs by workflow.
Spend per agent, user, session, workflow, and completed task.
Safety, relevance, accuracy, refusals, and regression trends.
Engagement, conversion, SLA health, and outcome impact.
Add lightweight client-side instrumentation to connect user experience with AI quality, latency, cost, and business outcomes.
Connect browser behavior to AI outcomes: sessions, clicks, product events, conversion signals, cohorts, and the AI interactions behind them.
Page views, clicks, sessions, and custom browser events
AI product interactions and conversation outcomes
Latency, errors, user behavior, and engagement signals
Conversion, retention, support, and business KPI events
Anonymous or identified user and cohort context
Use the linked guide to install the collector or SDK, verify the endpoint, and send a small trace or event payload. Once data lands, connect it to dashboards, evals, alerts, and investigations.
<script src="https://cdn.anosys.ai/pixel.js"></script>
<script>anosys.track("ai_task_completed", { outcome: "success" })</script>No. JavaScript and pixel monitoring are lightweight client-side ingestion paths. You can combine them with OpenTelemetry from backend services.
Yes. You control which browser events and attributes are sent, and enterprise controls can protect sensitive data.
Yes. Client-side behavior can be correlated with backend token and model cost to understand cost per product outcome.
Tool calls are usually captured from the backend, but AnoSys can correlate them with frontend sessions and user journeys.
Yes. Enterprise deployments can use governance, access controls, auditability, and sensitive data handling across product telemetry.