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Overview

Insights is the analytics home for your organization. Use it to monitor Copilot adoption and LLM spend, agent performance, workflow reliability, and API action volume.
In Apigene 5.16, Insights replaces the separate Dashboard page. Bookmarks to Dashboard open the same analytics under Insights.

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Accessing Insights

In the Design workspace, open Monitor → Insights (admin). Pick a tab and date range to load charts and tables.

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Tabs

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Date range

  • Quick presets (for example 7 / 30 / 90 days) plus custom start and end dates
  • Default: Last 30 days
  • Changing the range updates charts on the active tab (except where Agents uses its own agent-scoped controls)

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Conversations

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Activity

  • Threads over time
  • Threads by user (accounts that share the same email are counted as one user)
  • Average tokens per conversation
Use this to track Copilot adoption and spot power users or quiet periods.

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LLM usage and cost

  • Daily LLM usage with a cost / tokens toggle (input vs output)
  • Estimated spend by model and by provider
  • LLM usage by user
Costs are list-price estimates from known model pricing — useful for trends and chargeback, not an invoice. Pair with Settings to hide expensive models or add custom model IDs.

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Agents

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Org rollup

The Agents tab opens with a lightweight org summary:
  • Total interactions
  • Average duration
  • Success rate and error rate
  • Volume across agents

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Per-agent detail

Select an agent to load deeper charts and tables:
  • Totals and success rate
  • Response-time trends
  • Usage over time, peak days and hours
  • Application mix
  • Top and slowest actions
  • Cache performance (when caching is enabled)
  • User engagement
Empty or sparse charts usually mean little traffic in the selected range — widen the dates or confirm the agent is used in Copilot or via MCP.

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Workflows

  • Total runs, success rate, average duration, and runs waiting on approval
  • Runs over time and by status
  • Success rate and average duration over time
  • Breakdowns by workflow, agent, and user
  • Failures by step (where runs fail most often)
Pair with Workflow History to open a specific run and simulate it on the graph.

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Actions

  • Daily action volume and trends
  • Status-code mix (success vs client/server errors)
  • Usage by user and by application
Drill into Actions for request/response detail when investigating spikes or failures.

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Tips

  • Use shorter ranges for incident analysis; longer ranges for trends
  • Investigate slowest agent actions together with Actions history
  • If payloads look incomplete, check Interaction Recording
  • After fixing credentials or parameters, re-check Insights to confirm error rates drop