Manufacturing
An operating system for action, not just answers
Manufacturing data is fragmented across ERP, MES, quality systems, historians, and supplier portals, and Datafi connects it so every employee, from the plant floor to the boardroom, can investigate issues and act on them.
Manufacturing organizations aren't short on data. AI initiatives stall because production, quality, maintenance, and supply chain data live in separate worlds, and the people who need context can't assemble it fast enough.
ERP & Planning Systems
Production schedules, material requirements, cost data, and demand forecasts sit inside SAP, Oracle, or legacy ERP, so planners toggle between systems to reconcile plan against actual.
MES & Historians
Cycle times, OEE metrics, and process parameters are captured at the machine level but siloed from quality, maintenance, and business context, so operators see signals without causes.
Quality Systems
Inspection results, SPC data, non-conformance reports, and CAPA records live in dedicated platforms, so every root cause investigation starts with manual correlation across lots and shifts.
The Operating System
An operating system that turns AI from pilot to enterprise capability
A vertically integrated data and AI stack that provides trusted context, safe autonomy, and an interface that manufacturing teams actually adopt.
1 unified
Data Experience
Production, quality, maintenance, and supply chain data connected in a single governed interface
100% governed
By Design
Role-based access, audit trails, and policy enforcement across every AI interaction with operational data
Every role
Enterprise Wide
Plant managers, quality engineers, maintenance supervisors, planners, procurement leads, and finance leaders
Signal→ action
Not Just Answers
From detecting a variance to assembling context, identifying root cause, and recommending corrective action
Use Cases
Autonomous agents for high-impact manufacturing functions
Each workflow delivers a tangible business artifact: a root cause report, a quality investigation brief, a maintenance schedule, a risk assessment or an executive report. Every one is governed, auditable and ready for action.
Production Variance & Root Cause Analysis
From variance detected to root cause identified in minutes, not days
Every variance investigation means pulling data from MES, quality, maintenance, and ERP, often across shifts and lines. Datafi runs that as an agentic pipeline and delivers a traceable root cause report ready for corrective action.
Automated variance detection across production lines and shifts
Cross-system data assembly from MES, quality, maintenance, and ERP
AI-driven pattern analysis identifying contributing factors
Root cause reports generated with corrective action recommendations
Quality & Defect Tracing
Trace any defect to its source across the full production chain
Quality investigations span lot records, line configurations, supplier material data, process parameters, and inspection results across five or more systems. Datafi agents converge those streams into one traceability analysis that isolates root causes and defines containment scope.
Multi-source traceability across lots, lines, shifts, and suppliers
Defect clustering and pattern identification across production history
Supplier material correlation with quality outcomes
Quality investigation briefs with containment scope and recommended actions
Enterprise-Wide Impact
From the production floor to the boardroom
Datafi doesn't replace expertise. It amplifies it. Every role in the manufacturing organization gains the ability to reason across the full operational context, execute multi-step workflows, and produce real business outcomes.
Plant Manager
Monitors production, downtime, throughput, labor, and quality signals in one place, with AI-generated shift reports and exception alerts
Production Planner
Understands inventory constraints, supplier lead times, and customer demand without toggling across systems, and plans with full context
Quality Engineer
Traces defects across lots, lines, and shifts with all relevant context assembled, and investigates root causes in minutes, not days
Maintenance Supervisor
Prioritizes maintenance based on actual asset health, production impact, and cost avoidance, not just calendar schedules
Procurement Lead
Sees supplier risk, performance trends, and inventory exposure in real time, and acts on disruptions before they reach the floor
Finance Leader
Connects operational performance to margin, working capital, and forecast risk, and makes decisions grounded in full business context
The Platform
A complete stack purpose-built for manufacturing
Every layer of the Datafi platform serves a role in turning AI from isolated experiments into enterprise-wide manufacturing capability.
Outcomes
The operational impact manufacturing leaders measure
Manufacturers that deploy Datafi stop treating AI as an experiment and start treating it as infrastructure: faster root cause resolution, fewer unplanned stops, and better decisions at every level.
Faster Than Internal Builds
New workflows deploy in days instead of the quarters internal data teams spend building single-use dashboards and integrations.
More Capable Than Point Solutions
Manufacturing problems cross system boundaries, and Datafi connects the full context so AI can reason across quality, supplier, and process data at once.
Broader Than Copilot-Style Tools
Copilots answer questions about the data they can see; Datafi assembles context from MES, ERP, quality, maintenance, and supply chain, then recommends action.
Build AI into your manufacturing operating model
A practical, scalable path to faster root cause analysis, predictive maintenance, supply chain resilience, and operational excellence, powered by an operating system for business AI.