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Every flow, agent, and knowledge base includes a built-in Analytics page that provides comprehensive visibility into usage, performance, and costs. These analytics help you optimize AI operations, track resource consumption, and monitor system health.

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What’s Tracked

All AI operations are tracked and measured automatically. An AI operation is counted for:
  • Each node execution in a flow
  • Each message sent to or from an agent
  • Each file ingested into a knowledge base
Analytics data is available in real-time and can be filtered by time period, user, and specific resources.

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Flow Analytics

Flow analytics provide detailed insights into execution patterns, performance, and resource usage.
Flow Runs
  • Total runs (manual, triggered, and from agents)
  • Active runs currently executing
  • Run distribution over time
  • Runs per user
Performance
  • Average run time
  • Run time over time with percentile analysis (P25, P50, P90)
  • Active triggers
  • Error rate and error distribution over time
Token Tracking
  • Tokens & cost by AI model
  • Tokens & cost by node
  • Tokens & cost per user
  • Average cost per run
Cost Analysis All costs are estimated based on current model pricing from providers (OpenAI, Anthropic, Google, etc.). Actual costs may vary based on your agreements with providers.
  • Flow runs per user
  • Token usage per user
  • Cost attribution per user
  • Active users in the selected time period

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Agent Analytics

Agent analytics track conversational interactions, message volumes, and AI model usage.
Activity
  • Conversations started
  • Messages sent (user and agent messages)
  • Messages per conversation average
  • Active users
Trends
  • Conversations started over time
  • Messages sent over time
  • Conversations started per user
  • Messages sent per user
Token Tracking
  • Tokens & cost by AI model
  • Tokens & cost per user
  • Total chat estimated cost
Cost Breakdown Agent costs include all AI model interactions during conversations, including tool calls, knowledge base queries, and response generation.

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Knowledge Base Analytics

Knowledge base analytics monitor document ingestion, processing status, and user contributions.
Ingestion Status
  • Total documents uploaded
  • Documents processed successfully
  • Failed documents
  • Documents over time
Distribution
  • Documents per knowledge base
  • Documents by user
  • Document types (PDF, Word, Excel, etc.)
Contributors
  • Documents uploaded by user
  • Active contributors
  • User activity table with detailed breakdown

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AI Operations

AI operations represent the fundamental unit of resource consumption across the platform. What counts as an AI operation:
  • Flow Nodes: Each node execution (LLM calls, embeddings, AI processing)
  • Agent Messages: Each user message and agent response
  • KB Ingestion: Each file ingested and processed
AI operations are used for billing and quota management. Each workspace has AI operation limits based on its subscription tier.

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Workspace-Level Analytics

In addition to resource-specific analytics, workspace-level analytics provide a unified view across all flows, agents, and knowledge bases. Key Metrics:
  • Total AI operations used
  • AI models estimated cost
  • AI models total tokens
  • AI operations over time
  • Model tokens over time
  • AI operations per tool (flows, agents, KBs)
  • Model tokens per tool

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Accessing Analytics

Analytics are available in two locations:
  1. Resource-specific: Click the Analytics tab on any flow, agent, or knowledge base
  2. Workspace-level: Navigate to Workspace control > Analytics for aggregated metrics
Use time period filters to compare performance across different timeframes and identify trends.