Manufacturing Intelligence That Knows the Entire Line
Discrete manufacturing runs on complex interdependencies — machines, materials, schedules, quality specs, and supply chains. ElixirData's Context Graph maps these relationships so AI agents can optimize production, predict quality issues, and govern supply chain decisions with full traceability
The Challenge
Manufacturing AI Fails When It Can't See the Full Production Context
Factory floors generate massive data volumes from PLCs, MES, ERP, and quality systems. But AI agents that see only their slice — one machine, one process — miss the interdependencies that cause the most costly problems
Fragmented Production Visibility
Operational systems operate independently without shared manufacturing intelligence
PLC and MES disconnect
ERP schedule isolation
Quality data separation
Parameter change blindness
Work cell optimization bias
Outcome: Local optimization undermines overall production performance
Reactive Defect Detection
Quality issues are identified after value is added downstream in production
End-of-line inspection reliance
Late root cause discovery
Cross-process correlation gaps
Parameter-to-defect disconnect
Scrap and rework growth
Outcome: Higher defect costs and delayed corrective action
Context-Free Operational Decisions
Planning and procurement decisions lack full production visibility
Schedule and supplier disconnect
Lead time misalignment
Incoming material blind spots
Certification visibility gaps
Partial information decisions
Outcome: Production delays and avoidable supply disruptions
How It Works
How AI Agents and Context Graph Transform Manufacturing
ElixirData compiles the digital twin of your production environment — machines, materials, processes, quality specs, and supply chains — into a Context Graph that AI agents reason over in real-time
Unified End-to-End Manufacturing Graph
AI agents see complete cross-process production dependencies
Machine and work cell dependency mapping
Real-time process parameter tracking
Material lot genealogy visibility
Schedule and resource interdependency modeling
Decisions reflect full production chain cause-and-effect relationships
Authority-Constrained Production Optimization
Optimization executes only within defined operational authority limits
In-spec parameter auto-adjustment controls
Engineering approval for out-of-spec changes
Planning authority for schedule modifications
QA-controlled quality hold enforcement
Production agility without compromising governance or quality control
Complete Production Decision Records
Every production action is captured with full contextual evidence
Process parameter adjustment documentation
Quality evaluation decision traces
End-to-end lot genealogy records
Regulatory and audit evidence generation
Full traceability from raw material to finished goods
Capabilities
What ElixirData Delivers for Discrete Manufacturing
ElixirData enables manufacturers to synchronize production, quality, maintenance, and supply chain decisions through a unified Context Graph with structurally governed AI agents
Real-Time Production Optimization
AI agents continuously monitor machine availability, material readiness, order sequencing, and quality signals across the full production environment
Parameter adjustments and line balancing execute within defined engineering authority limits and operational constraints
Higher throughput with controlled, policy-aligned production adjustments
Predictive Quality Intelligence
The Context Graph correlates multi-stage process parameters with downstream inspection and performance outcomes
AI predicts defect risks before occurrence, identifying parameter combinations that historically drive quality drift
Fewer defects and earlier, data-driven quality interventions
Supply Chain Context
Supplier lead times, certifications, inventory positions, and production schedules are unified in a single contextual model
Procurement decisions reflect production priorities, while scheduling decisions account for real material availability
Reduced shortages and tighter alignment between supply and production
Governed Maintenance Decisions
AI analyzes vibration trends, cycle counts, and quality degradation signals within full production context
Maintenance scheduling occurs within production constraints and follows defined maintenance authority approval levels
Lower downtime with maintenance aligned to operational priorities
Lot Genealogy & Traceability
The Context Graph captures complete lineage from raw materials through process parameters to final inspection results
Every transformation step is recorded, enabling rapid trace-back and regulatory documentation
End-to-end traceability supporting compliance and customer transparency requirements
OEE & Performance Analytics
Real-time OEE is computed from integrated production, downtime, and quality data sources
AI identifies root causes of availability, performance, and quality losses with contextual evidence
Measurable performance improvements driven by evidence-based corrective actions
Use Cases
Discrete Manufacturing Scenarios
See how governed AI agents and the Context Graph coordinate production, quality, supply chain, and compliance decisions across the full manufacturing lifecycle
Integrations
Connects to Your Discrete Manufacturing Stack
ElixirData seamlessly integrates with the tools your development teams already use, including code generation, testing frameworks, security scanners, and deployment platforms
MES/MOM
ERP
Automation
Quality
FAQ
Frequently Asked Questions
The Context Graph unifies OT and IT data, enabling AI to correlate machine processes with business requirements and eliminate data silos
Parameter adjustments within approved ranges auto-execute; out-of-spec changes are blocked, requiring review, with all actions fully traced for accountability
The Context Graph enables multivariate quality prediction, detecting parameter interactions across work cells that SPC misses, predicting defects before they occur
Yes. Decision Traces capture parameter settings, material lineage, quality data, and rationale in real time, meeting FDA, GMP, and 21 CFR Part 11 requirements
Ready to Transform Discrete Manufacturing?
See how ElixirData's Context OS and AI agents deploy in your discrete manufacturing environment in 4 weeks