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Business Process Monitoring

Business process monitoring lets teams observe AI-assisted and human-in-the-loop workflows as production systems. Anosys can ingest, monitor, analyze, evaluate, and root-cause business processes so client pain points can be resolved quickly.

What It Does

Anosys connects process events, AI traces, application telemetry, user behavior, evals, cost, and business KPIs into one operational timeline. It can monitor process health, SLA status, bottlenecks, outcome quality, ownership, and root cause.

When To Use It

Use it for:

  • Claims, onboarding, underwriting, ordering, fulfillment, and back-office workflows.
  • Support escalations and customer success operations.
  • Agent-assisted business processes.
  • SLA monitoring and operational reporting.
  • Finding where clients are blocked or delayed.

Prerequisites

  1. Define the process steps and success outcome.
  2. Send events with process identifiers.
  3. Add timestamps, state changes, owners, customer impact, and outcome fields.
  4. Create process units for the workflows you want to monitor.

Step-By-Step Setup

  1. Send process events through REST, OpenTelemetry, SDKs, or file ingestion.
  2. Create a Process Unit for each monitored workflow.
  3. Define success, failure, warning, and timeout states.
  4. Add evals for quality or policy checks.
  5. Build dashboards for process health and SLA status.
  6. Add alerts for bottlenecks, failed steps, or client-impacting regressions.

Example Event

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{
  "process": "claims-review",
  "process_id": "claim_9182",
  "step": "ai_document_review",
  "status": "completed",
  "duration_ms": 18200,
  "owner": "claims-ops",
  "customer_tier": "enterprise",
  "outcome": "approved"
}

What Appears In The Console

You will see process-unit health, timelines, failed steps, bottleneck analysis, SLA status, related traces, eval results, alerts, and summaries for operations teams.

Common Mistakes

  • Sending events without process IDs.
  • Tracking steps but not outcomes.
  • Monitoring process timing without ownership or customer impact.
  • Treating AI agent telemetry separately from business process telemetry.