ManufacturingAI Agents & AutomationData & Intelligence
Multi-Agent System for 24/7 Manufacturing Plant
Fixed-fee Sprint + Monthly Retainer
31%
Reduction in unplanned downtime · 90 days
The challenge
A 3-shift sheet-metal plant with 40+ CNC machines and ~120 operators. Reactive production: machines went down, operators flagged supervisors, maintenance scrambled. Average downtime per incident was 2.4 hours. Predictive maintenance had been talked about for years — the data was rich but siloed across SCADA, ERP, and operator log sheets.
The approach
- Mirror the org chart: one agent per role a human would fill if you had infinite humans
- Six specialized agents communicate through a shared event bus
- Every alert routes to a human via WhatsApp + the existing supervisor dashboard — humans make every call
The build
- LangGraph orchestration · one agent per role · shared Postgres event bus
- Real-time data: Kafka stream from SCADA + Alian Infinity ERP API + operator-tablet inputs
- Classical ML (LightGBM) for downtime prediction per machine class, retrained weekly
- Alert routing via WhatsApp Business API
- Edge gateway on-prem (latency + data residency); agent reasoning in cloud
The results
- 31% reduction in unplanned downtime (14.2 → 9.8 hrs/week)
- Mean time to detect anomaly: 18 min → 2.3 min (8x faster)
- Maintenance backlog cleared 67%
- Zero stockouts in 90 days (vs 7 in the prior 90)
- Energy cost down 9% from sequencing optimizations alone
"I expected a fancy dashboard. What we got was a team of agents that quietly do the watching so my humans can focus on doing."
Tech stack
- Anthropic Claude Sonnet
- LangGraph
- Kafka
- Postgres
- LightGBM
- WhatsApp Business API
- Alian Infinity ERP
- Langfuse
Why this matters for you
Multi-agent systems are where AI is going. This is a working production deployment — not a demo, not a pilot.
Want a build like this?
20 min. No deck. We'll tell you whether this pattern fits your situation, and what an honest scope looks like.
