# Measure operating reality.

> Plan operational analytics around execution outcomes, approvals, policy decisions, capability use, target health, latency, and evidence quality.

Canonical: https://rangoon.ai/product/analytics/

Status: In active development. Product screenshots are design previews with illustrative data. No general availability is implied.

## Metrics that guide action

The planned view includes successful and failed runs, blocked actions, approval rate, policy violations, utilization, compatibility, and connector reliability.

### Trace to a decision

A useful metric should help an operator improve a workflow, policy, target, or capability.

## Understand distribution

Intended reporting can show how skills, workflows, agents, models, connectors, and harnesses are actually used.

### Context matters

Estimated costs and token consumption should be interpreted alongside outcomes and target behavior.

## Keep claims grounded

Preview metrics in design imagery are sample data and should not be read as customer, production, or performance evidence.

### Active development

Analytics implementation and data contracts remain under development.


## More information

- [Documentation index](https://rangoon.ai/llms.txt)
- [AI access and policies](https://rangoon.ai/ai/)
- [Source repository](https://github.com/hypler-dev/rangoon)