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Monitoring & Analytics

Telemetry & Metrics Dashboard

Track AI tool usage and performance in real-time. You can't improve what you don't measure. A telemetry dashboard gives you visibility into how AI is being used across your organization.

What Is a Telemetry & Metrics Dashboard?

A telemetry and metrics dashboard collects and displays real-time data about AI tool usage across your organization. It tracks who is using AI tools, how often, for what purposes, and how well those tools are performing.

This visibility helps you understand adoption patterns, identify power users, spot underutilized tools, and catch problems before they become critical issues.

Why It Matters

Measure Adoption and ROI

Track which teams are adopting AI tools and quantify the business value they're generating.

Identify Performance Issues

Catch slow response times, high error rates, and other problems before users complain.

Optimize Resource Allocation

See which tools are heavily used and need more capacity versus which are underutilized.

Support Data-Driven Decisions

Make investment and prioritization decisions based on actual usage data, not guesswork.

Key Metrics to Track

Active Users

Daily, weekly, and monthly active users by department, team, and tool.

Usage Frequency

How often users engage with AI tools and which features they use most.

Performance Metrics

Response times, error rates, success rates, and system availability.

Cost per Transaction

API costs, compute usage, and per-user or per-query expenses.

Quality Scores

User satisfaction ratings, thumbs up/down feedback, and output quality metrics.

Adoption Trends

Growth in user base, feature adoption curves, and retention rates.

Maturity Levels

Not Started / Planning

No visibility into AI tool usage. No metrics collection. Decisions based on anecdotes and assumptions.

In Progress / Partial

Basic usage logging in place. Manual reports generated periodically. Limited real-time visibility.

Mature / Complete

Real-time dashboard with comprehensive metrics. Automated alerts for issues. Regular review meetings with stakeholders using data-driven insights.

How to Get Started

  1. 1.
    Define Key Metrics: Start with 5-10 metrics that matter most to your business (users, usage, costs, performance).
  2. 2.
    Instrument Your Tools: Add logging and tracking to AI applications to capture usage data.
  3. 3.
    Choose a Dashboard Platform: Use existing tools like Grafana, Datadog, or build custom dashboards with your BI platform.
  4. 4.
    Set Up Automated Reporting: Create scheduled reports for stakeholders who don't need real-time access.
  5. 5.
    Establish Review Cadence: Schedule regular reviews of metrics with leadership to act on insights.

Ready to Gain Visibility Into Your AI Usage?

Get expert help setting up telemetry and metrics dashboards that provide actionable insights into your AI implementations.