Back to feed
Dev.to
Dev.to
7/26/2026
The original title is: "Evidence First, Answer Second: Building an Observable Industrial AI Agent with SigNoz"

The original title is: "Evidence First, Answer Second: Building an Observable Industrial AI Agent with SigNoz"

Original: Evidence First, Answer Second: Building an Observable Industrial AI Agent with SigNoz

Short summary

The author builds an industrial IoT anomaly control system for a simulated water-treatment plant that uses AI agents to detect equipment issues, search a knowledge base, and either recommend safe actions or escalate to humans based on evidence confidence. SigNoz provides full observability of the agent's decision path from sensor reading to final recommendation. The system distinguishes bad telemetry from broken machines, groups related alerts into single investigations, and uses measurable confidence signals rather than LLM-generated confidence numbers.

  • •Industrial AI agent for water-treatment plant monitoring with evidence-based escalation
  • •SigNoz observability exposes full agent decision path from sensor to recommendation
  • •Confidence calculated from measurable signals, not LLM-generated percentages

Generated with AI, which can make mistakes.

#ai-agents#ai-tools#open-source
Read full article at Dev.to

Is this a good recommendation for you?

Comments

Failed to load comments. Please try again.

Explore more

The original title is: "Adding Observability to a LangGraph Multi-Agent Pipeline with SigNoz"
Dev.to
The original title is: "Building AXRAY: Observability for AI Coding Agents with SigNoz and OpenTelemetry"
Dev.to
The original title is "Building Missio: An Evidence-Bound Remediation Agent with SigNoz"
Dev.to
The original title is about AI agents handling money and the need for proper instrumentation. Let me rewrite this for a mobile feed.
Dev.to