Predictive Maintenance
- Vibration analysis
- Failure prediction
- Maintenance scheduling
- Spare parts inventory
SHEET 01ManufacturingPRODUCTION
AI agents that run production lines, not just monitor them.
Deploy agents across production lines, equipment monitoring, and supply chains. Get real-time OEE visibility, predictive maintenance, autonomous scheduling, and quality control that prevents defects before they happen, without manual intervention.
Active Lines8
Avg OEE82.4%
Output Today3,179
LineProductOEEOutputStatus
L-01X-420087.2%1,247Running
L-02K-180091.5%892Running
L-03X-420068.3%412Changeover
L-04M-3100—0Maintenance
L-05K-180074.8%628Running
8 active lines 82.4% avg OEE 3,179 output today
35%Less unplanned downtime
10M+Data points monitored
90%Defect detection rate
<3 wksTo production
SHEET 02Manufacturing Execution Lifecycle5 STAGES
From sensor data to operational decisions in real time.
Agents ingest data from IoT sensors, PLCs, and SCADA systems, then predict equipment failures, optimize schedules, control quality, and generate work orders. Full lifecycle coverage from sensor ingestion to production output.
Definition
AI agents for manufacturing are autonomous systems that monitor production lines, predict equipment failures, optimize scheduling, detect quality defects, and manage supply chain risk. They connect to ERP, MES, SCADA, IoT, and quality management platforms to maintain continuous operational visibility across discrete and process manufacturing environments.
01Sensor Ingest
IoT, PLC, SCADA data streams
02Context Engine
Unified production data model
03Predictive Analysis
Maintenance, quality, demand
04Execute & Control
Schedule, route, alert, act
05Operation Outputs
OEE, work orders, dashboards
5 stages 82.4% avg OEE <200ms latency
SHEET 03OEE Performance Analytics5 LINES
Equipment effectiveness and production performance at a glance.
Agents aggregate OEE data across every production line, breaking down availability, performance, and quality to surface bottlenecks and drive continuous improvement. Real-time visibility into your factory floor.
LineAvailPerfQualOEETrend
L-0192.1%95.9%98.7%87.2%High
L-0294.3%97.2%99.8%91.5%High
L-0378.4%88.1%98.9%68.3%Low
L-04————Offline
L-0584.2%90.1%98.6%74.8%Medium
82.4% avg OEE 2 high 1 medium 1 low 1 offline
SHEET 04Use CasesMANUFACTURING
What you can automate across the factory floor.
From quality inspections to supply chain dashboards, see how AI agents solve real problems across discrete and process manufacturing.
UC-01
Employee IT & HR Helpdesk
Automate internal support for IT tickets, HR policy questions, benefits inquiries, and onboarding tasks. Agents pull answers from internal wikis and escalate to the right team when needed.
UC-02
Voice Quality Inspections & Field Reporting
Field workers report quality checks, safety observations, and maintenance findings by voice. Agents transcribe, categorize, and file structured reports in your compliance system.
UC-03
Automated Invoice Processing
Extract line items, PO numbers, and payment terms from invoices in 90+ formats. Auto-match against purchase orders, flag discrepancies, and route for approval — 85% straight-through processing.
UC-04
Supply Chain Performance Dashboards
Monitor inventory levels, supplier lead times, and fulfillment rates in real time. Agents detect bottlenecks, predict stockouts, and recommend reorder actions before disruptions hit.
UC-05
Intelligent Vendor Management
Centralize vendor onboarding, contract tracking, performance scoring, and renewal management. Agents extract terms from agreements, monitor SLAs, and flag underperformance automatically.
UC-06
Automated Employee Onboarding
Orchestrate the full onboarding journey: document collection, system provisioning, policy acknowledgement, training scheduling, and 30/60/90-day check-ins — all managed by AI agents.
SHEET 05Manufacturing Intelligence ArchitectureGOVERNED
Every production decision passes through governed execution.
Full audit trail. Safety guardrails enforced. Agents operate under manufacturing governance that operations leaders and regulatory bodies trust.
01ERP & MES Systems
SAP, Oracle, Siemens Opcenter
02Context Engine
Unified production data model
03AI Operations
Predict, schedule, optimize
04Governance Layer
Safety, compliance, audit
05Mfg Outputs
OEE, work orders, reports
Quality Control
- Defect detection
- SPC chart monitoring
- Root cause analysis
- Batch traceability
Supply Chain
- Supplier risk scoring
- Inventory optimization
- Lead time tracking
- Logistics visibility
Production Planning
- Demand forecasting
- Capacity planning
- Shift scheduling
- OEE optimization
35%Less downtime
10M+Data points monitored
<200msDecision latency
99.95%Uptime SLA
SHEET 06Manufacturing Integration Ecosystem65+ SYSTEMS
Connect to your entire factory technology stack.
Assistents integrates with ERP, MES, SCADA, IoT platforms, and more. Agents build a unified production view using our Context Engine.
CategorySystemsCountSync mode
ERP & MESSAP, Oracle, Siemens Opcenter12Bidirectional
IoT & SensorsAzure IoT, AWS IoT, PTC ThingWorx10Bidirectional
SCADA & PLCRockwell, Honeywell, Schneider8Bidirectional
Quality MgmtInfinityQS, ETQ, MasterControl9Read + Sync
Supply ChainKinaxis, Blue Yonder, Coupa11Read + Sync
AnalyticsTableau, Power BI, Grafana15Read-only
65+ pre-built connectors for manufacturing systems. Open APIs for custom integrations. Explore all integrations
SHEET 07Specification NotesFAQ
Questions manufacturing leaders ask
How does AI improve manufacturing OEE?
AI agents monitor Overall Equipment Effectiveness in real time by tracking availability, performance, and quality metrics across production lines. They identify bottlenecks, predict failures before they occur, and recommend optimizations — increasing OEE by 15-25% on average.
Can AI agents predict equipment failures?
Yes. Predictive maintenance agents analyze sensor data, vibration patterns, temperature readings, and historical failure data from 10M+ data points. They identify degradation patterns and alert maintenance teams before failures occur, reducing unplanned downtime by up to 35%.
How does AI handle quality control?
Quality agents monitor production data in real time, detect defects and anomalies, trace root causes across the production chain, and trigger corrective actions automatically. They achieve 90%+ defect detection rates while reducing manual inspection time.
Can AI agents integrate with SCADA and MES systems?
Yes. assistents connects with SCADA, MES, ERP (SAP, Oracle), CMMS, PLM, and IoT platforms through 65+ pre-built manufacturing connectors. Data stays within your infrastructure with on-premise deployment options for air-gapped environments.
How quickly can manufacturing AI agents be deployed?
Most manufacturing organizations go from initial setup to production in under 3 weeks. We start with a focused use case like predictive maintenance or OEE monitoring, connect to your systems, and validate outcomes before scaling across the plant floor.
SHEET 08Sign-offREADY
In production in 3 weeks.
Start with predictive maintenance, OEE monitoring, or supply chain intelligence. We will connect to your systems, enforce your safety controls, and deliver measurable outcomes in weeks.
- Audience
- Manufacturing · Operations leaders
- Platform
- 65+ integrations · On-premise option
- Lead time
- Setup to production · 3 weeks
- Sheet
- 8 of 8 · Manufacturing
See the Manufacturing Demo
Watch agents monitor production lines, predict failures, and optimize scheduling in real time.
Schedule demoConnect your factory systems
Explore how assistents integrates with ERP, MES, SCADA, and IoT platforms across your operations.
See integrationsAI Agents vs RPA
Learn why agentic AI outperforms legacy RPA for manufacturing automation, quality control, and supply chain management.
Read the comparison