Connect Without Replacing
Build intelligence around existing infrastructure while retaining established operational systems.
Factory Intelligence Beyond Boundaries
Your Factory. Connected. Intelligent. Predictive.
FactoryDone.ai connects your machines, enterprise systems, and manufacturing operations through an intelligent AI layer—transforming industrial data into actionable insights, predictive maintenance, smarter planning, and automated workflows.
- Connect Existing Systems
- Predict Equipment & Operational Risks
- Act on AI-Driven Intelligence
Built for manufacturing enterprises. Designed to work with existing industrial and enterprise systems.
- SourceMachines & SensorsPLCs, telemetry, IIoT devices
- SystemsSCADA · Historian · ERPExisting OT and IT applications
- Intelligence
FactoryDone.ai layerContext, analytics, industrial AI - OutcomePredict · Recommend · ActAlerts, recommendations, governed workflows
Connected factory intelligence platform
One Intelligence Layer. Across Your Entire Factory.
Turn disconnected industrial and enterprise data into one intelligent operational view—without replacing the systems you already rely on.
How the intelligence layer is built
Layer 1Factory & Enterprise Data
- Machines
- Sensors
- PLCs
- SCADA
- ERP
- MES
- Historians
- Databases
Layer 2FactoryDone.ai Integration
- Secure data connectivity
- Asset context
- Data unification
- Event processing
Layer 3Industrial AI Intelligence
- Anomaly detection
- Predictions
- Analytics
- AI agents
- Knowledge intelligence
- Recommendations
Layer 4Operational Execution
- Maintenance workflows
- Production planning
- Traceability
- Alerts
- Reports
- Human approvals
FactoryDone.ai connects OT and IT environments and turns the combined data into operational intelligence. It runs as an integration and intelligence layer across your existing applications, industrial assets and production workflows.
Industrial OT systems
Shop-floor control, telemetry and historian data.
- PLCs
- SCADA
- DCS
- IIoT sensors
- Edge gateways
- OPC UA
- MQTT
- Modbus TCP
- Industrial historians
- Machine telemetry
- Equipment monitoring systems
Enterprise IT systems
Asset masters, orders, inventory and plant records.
- SAP
- SAP Business One
- ERPNext
- Microsoft Dynamics 365
- Oracle NetSuite
- Custom ERP
- MES applications
- CMMS systems
- SQL & enterprise databases
- REST APIs
- Enterprise data platforms
These are integration capabilities and potentially compatible systems. Availability of a specific connector depends on your infrastructure, licensing and implementation scope; not every integration is certified or plug-and-play.
Differentiator
Start with the data you already have.
FactoryDone.ai does not depend on installing new sensors in every scenario. Where usable machine telemetry already exists in SCADA, PLCs or historians, the platform integrates with it directly. Where additional condition-monitoring data is needed, sensors and edge connectivity are added as part of the solution.
Unified Operational Visibility
Bring asset, maintenance, production, and enterprise information into one context.
AI-Powered Decision Support
Turn machine events and operational data into prioritized recommendations.
Intelligent Workflow Automation
Connect insights to alerts, maintenance requests, planning decisions, and review workflows.
Flexible Deployment Architecture
Designed to support cloud, hybrid, and on-premises deployment requirements, subject to infrastructure and implementation design.
Enterprise Governance
Role-based access, controlled integrations, auditability, and human approval for consequential actions.
◆ Flagship module · Smart Maintenance & Asset Reliability
From Reactive Maintenance to Predictive Reliability.
Manage the complete equipment maintenance lifecycle—from asset onboarding and preventive scheduling to real-time condition monitoring, anomaly detection, failure risk insights, and AI-assisted maintenance decisions.
Equipment health trend · Compressor C-204 · velocity RMS
Vibration spectrum (FFT) · Pump P-204 DE bearing
Work orders · this week
12Open
5In progress
2Overdue
18Closed
Upcoming preventive maintenance
- C-204 bearing inspectionPlanned
- Boiler B-01 burner serviceReady
- M-112 spindle lubricationParts due
AI equipment insight
Spectral peaks at 88.6 Hz and its 2nd harmonic match the outer-race defect frequency (BPFO) for the P-204 drive-end bearing. Pattern is consistent with early-stage outer-race wear.
Evidence: FFT 08 Oct · 3 similar cases · OEM manual §7.2
Risk prioritization
| Asset | Condition signal | Criticality | Priority | Health |
|---|---|---|---|---|
| Compressor C-204 | Vibration velocity above limit, rising | A · line-stopping | High | 38 |
| Pump P-204 | BPFO peaks in spectrum | B · redundant standby | Medium | 57 |
| Chiller CH-02 | Discharge temperature drifting +3.1 °C | B · process cooling | Medium | 71 |
| CNC Mill M-112 | Spindle load within baseline | A · bottleneck cell | Monitor | 86 |
All values above are illustrative sample data and do not represent a customer deployment.
The intelligent maintenance suite
Each module works on its own and gets stronger with the others. Asset records, schedules, work history and condition data share one context, so every alert arrives with the information an engineer needs to act.
Asset Management
A single, structured record for every plant, line, machine and component. Equipment records can be mapped and synchronized with enterprise systems such as SAP, ERPNext, Microsoft Dynamics and other ERPs through appropriate integrations.
- Centralized asset registry
- Asset hierarchy and classification
- Equipment master data management
- Plant, line, machine and component mapping
- Equipment criticality
- Asset lifecycle records
- Maintenance history
- Equipment documents and technical manuals
- Spare parts association
- QR-based asset identification where supported
- ERP asset master synchronization
- Equipment-specific operational history
Preventive Maintenance
Keep maintenance proactive, structured, and accountable.
- Planned maintenance programs
- Daily, weekly, monthly, quarterly and annual schedules
- Time-based maintenance
- Meter-based and usage-based maintenance
- Recurring inspections
- Maintenance checklists
- Work-order generation
- Technician assignments
- Maintenance calendars
- Escalations and notifications
- Overdue task tracking
- Approval workflows
- Maintenance compliance tracking
- Maintenance execution records
Corrective & Breakdown Maintenance
Capture every failure. Learn from every repair.
- Breakdown reporting
- Incident registration
- Corrective maintenance work orders
- Failure classification
- Root cause documentation
- Repair history
- Downtime tracking
- Technician assignment
- Repair completion validation
- Parts consumption
- Failure recurrence analytics
- Mean Time to Repair (MTTR)
- Mean Time Between Failures (MTBF)
Condition Monitoring
Connect equipment operating parameters from available SCADA, historian, PLC, IoT gateway or installed sensor data. Analysis runs in real time or periodically, depending on how the data is available.
- Vibration
- Temperature
- Motor current
- Pressure
- Flow
- RPM
- Electrical load
- Energy consumption
- Acoustic signals*
- Other machine telemetry
* Where suitable instrumentation is available.
Spare Parts & Maintenance Planning
Make sure the right parts are ready before the work starts, with inventory visibility drawn from your ERP.
- Spare part catalogs
- Equipment-to-spare mapping
- Parts availability
- Inventory visibility through ERP integration
- Parts usage history
- Maintenance material requirements
- Spare readiness before planned maintenance
- Parts consumption tracking
- Replenishment recommendations based on supported data
- Maintenance planning coordination
Maintenance Analytics
Reliability and maintenance performance in one view, at asset, line and plant level.
- Asset availability
- Planned vs. unplanned maintenance
- Maintenance compliance
- MTTR
- MTBF
- Downtime trends
- Equipment health trends
- Maintenance backlog
- Failure frequency
- Maintenance cost visibility where data is integrated
Module E · Predictive Maintenance & Industrial AI
Ten levels of condition intelligence, applied where the data supports them.
Start with configurable limits and grow into statistical, spectral and model-based analytics as data history builds. Each method is applied according to the data available for that asset.
Rule-based → data-supported prediction
- 01
Threshold-Based Monitoring
Rule-based equipment condition alerts and configurable operating limits.
- 02
Statistical Anomaly Detection
Deviations in equipment behavior identified from baselines, trends and statistical analysis.
- 03
Vibration Analytics
Time-domain and frequency-domain analysis of equipment vibration signals.
- 04
FFT & Spectrum Analysis
Frequency-spectrum visualization that highlights abnormal characteristics which may indicate bearing defects, imbalance, misalignment or other mechanical conditions.
- 05
Condition Trend Analysis
Degradation signals and changes in operating behavior tracked over time.
- 06
Predictive Failure Risk Analysis
Elevated failure risk estimated from historical and operating data where data of sufficient quality exists.
- 07
Remaining Useful Life Estimation
Supported where appropriate data and validated models are available.
- 08
AI-Assisted Root Cause Analysis
Correlates operating conditions, past failures, maintenance records and technical documents to support diagnosis.
- 09
AI Maintenance Recommendations
Suggested inspections, probable causes, troubleshooting steps, priority and maintenance actions.
- 10
Intelligent Alert Prioritization
Issues ranked by asset criticality, severity, observed conditions and operational impact.
Spectrum analysis is a diagnostic aid, not a stand-alone failure predictor. Failure risk and remaining useful life estimates depend on adequate training and validation data, and their accuracy is established per asset class during implementation.
Module F · Intelligent Maintenance Execution
From signal to closed work order, with engineers in control.
Condition intelligence flows straight into maintenance workflows. AI provides explainable suggestions with the evidence behind them, and human approval stays in place for operationally consequential decisions.
- Signal detectedTelemetry crosses a limit or deviates
- Analyze abnormalityTrend, spectrum, context
- Evaluate equipment riskCriticality and impact
- Generate recommended actionWith supporting evidence
- Engineer reviewAccept, adjust or reject
- Create & assign work orderParts and crew checked
- Execute & closeChecklist and sign-off
- Capture feedbackImproves future recommendations
Human decision point
AI-driven manufacturing operations
Beyond Maintenance. Intelligence for Every Manufacturing Operation.
Connect production, planning, traceability, and operational decision-making through one extensible industrial intelligence platform.
Production Planning & Scheduling
AI-assisted production planning that accounts for machine availability, material supply and capacity constraints, with planners reviewing and approving every change.
- Production order visibility
- Work-center and machine allocation
- Resource capacity analysis
- Production schedule coordination
- Material availability analysis
- Production bottleneck identification
- Machine availability considerations
- Supply constraint identification
- Schedule risk alerts
- AI-assisted rescheduling recommendations
- What-if planning scenarios
- Planner review and approval
Example scenarioA critical component is delayed, putting customer orders at risk. FactoryDone.ai identifies impacted production schedules, evaluates feasible alternatives, and recommends a revised production plan for planner approval.
Manufacturing Traceability
Know what was made, where it was made, how it moved, and which materials and processes were involved.
- Material and batch traceability
- Lot and serial tracking
- Work-in-progress visibility
- Production process history
- Raw material to finished goods genealogy
- Machine and production-order association
- Operator and process-event records
- Quality event association
- Multi-stage process visibility
- Forward and backward traceability
- ERP/MES synchronization
- Audit-ready trace records, dependent on captured data
Factory Operations Intelligence
Move beyond dashboards that show what happened—to intelligence that helps teams decide what to do next.
- Operational performance dashboards
- Machine utilization
- Production visibility
- Downtime categorization
- OEE analytics where accurate source data exists
- Cycle time variance
- Throughput trends
- Production loss insights
- Bottleneck analysis
- Energy and asset performance analytics
- Plant and multi-plant reporting
- Exceptions and operational alerts
Industrial AI Copilot & Agentic Workflows
A manufacturing-aware assistant grounded in your integrated operational data. It answers questions, explains anomalies and proposes actions, and it triggers workflows only within the approvals you define.
- Natural-language factory analytics
- Questions across connected operational data
- Equipment maintenance knowledge assistant
- Historical operating information queries
- Technical documentation retrieval
- Anomaly explanations
- Production and maintenance summaries
- Recommended corrective actions
- Emerging operational risk identification
- Planning alternatives
- Governed workflow triggers
- Approval-based automation
Ask your factory a question.
The copilot is context-aware: it reads from connected maintenance history, asset context, equipment readings and enterprise knowledge, cites what it used, and leaves the decision with your team.
Questions teams ask:
- “Which machines have the highest downtime this week?”
- “Which scheduled maintenance activities could affect tomorrow's production?”
- “How will a two-day supplier delay affect production orders?”
- “Summarize this month's maintenance performance.”
AI that goes past the chart.
FactoryDone.ai converts connected factory data into a decision sequence your teams can follow and audit.
- Detect
Spot deviations in machine, process and order data as they happen.
- Understand
Add asset context, history and documentation to explain the signal.
- Predict
Estimate risk and likely impact where the data supports it.
- Recommend
Propose prioritized, explainable actions with evidence.
- Act
Trigger governed workflows after human approval.
Book a demo
Make Your Factory More Intelligent.
Discover how FactoryDone.ai can connect your existing factory systems, improve maintenance reliability, and bring actionable intelligence into your manufacturing operations.
India · Headquarters
No 15, Lakshmi Gardens,
Ramakrishna Puram, Ganapathi,
Coimbatore, Tamil Nadu 641006 +91 78128 07079 United States 539 W Commerce St #4403,
Dallas, TX 75208,
USA +1 313 444 7009
Ramakrishna Puram, Ganapathi,
Coimbatore, Tamil Nadu 641006 +91 78128 07079 United States 539 W Commerce St #4403,
Dallas, TX 75208,
USA +1 313 444 7009
FactoryDone.ai is developed by Xyloite Technologies Private Limited.
Request your demo
Tell us about your plant and the problem you want to solve. Fields marked * are required.