Guide

Analytics for AI Assistants

What to log, how to review conversations, and how to translate model behavior into product decisions and operational insights.

Why analytics matters

High-performing assistants get better through feedback and measurement, not just better prompts.

Logging and analytics help you measure assistant quality, identify breakdowns, and focus your improvement cycles on what matters.

Without analytics, teams rely on anecdotal signals — and the assistant never improves in predictable ways.

Phase 1. Logging the right events

The goal is to capture signals that describe assistant behavior and user satisfaction.

Phase 2. Reviewing conversations

Use structured workflows to turn logs into decisions.

Want help setting up assistant analytics?

We help teams build logging pipelines, golden sets, evals, and dashboards that track real assistant performance.

If you want a system that provides clarity — and predictable improvement cycles — we can build it with your team.

Talk to us about analyticsExplore services & training options

Includes discovery, pipeline setup, dashboards, and training.