The smartest factories don’t wait to react. They adapt in motion.
The smartest factories don’t wait to react. They adapt in motion.
Xenese™ enables AI that acts at the edge and proves
every move across your operations.
Xenese™ enables AI that acts at
the edge and proves every move
across your operations.
Solutions
Solutions
Manufacturing Solutions
Manufacturing Solutions
Streamline your value chain with real-time decisions that reduce risk and increase resilience.
Streamline your value chain with real-time decisions that reduce risk and increase resilience.
Entity-Level Edge
Predictive
Maintenance
Entity-Level Edge
Predictive
Maintenance
Business Challenge
Legacy predictive maintenance platforms rely on centralized models, delaying insights and overlooking machine-specific failure signatures. At the industrial edge—where connectivity is limited and precision matters—this approach breaks down.
Business Challenge
Legacy predictive maintenance platforms rely on centralized models, delaying insights and overlooking machine-specific failure signatures. At the industrial edge—where connectivity is limited and precision matters—this approach breaks down.
Xenese™ Solution
Xenese builds and deploys per-asset, real-time ML models directly at the edge—on machines, gateways, or facility servers. Each model learns that asset’s unique behavior (vibration, pressure, current, torque), adapting autonomously using in-memory processing and sliding time window analysis. GenAI orchestrates task assignments, parts sourcing, and work orders across facilities. All data, scoring, and interventions are cryptographically recorded for audit, compliance, and RCA transparency.
Xenese™ Solution
Xenese builds and deploys per-asset, real-time ML models directly at the edge—on machines, gateways, or facility servers. Each model learns that asset’s unique behavior (vibration, pressure, current, torque), adapting autonomously using in-memory processing and sliding time window analysis. GenAI orchestrates task assignments, parts sourcing, and work orders across facilities. All data, scoring, and interventions are cryptographically recorded for audit, compliance, and RCA transparency.
Key Results
Key Results
%
reduction in unexpected failures at high-value assets
%
reduction in unexpected failures at high-value assets
%
decrease in maintenance overhead
%
decrease in maintenance overhead
%
faster triage and part-match coordination
%
faster triage and part-match coordination
Digital Twin
Production
Optimization
Business Challenge
Inefficient line configurations and inventory delays cause bottlenecks and material waste. Legacy systems cannot simulate process options in real time.
Xenese™ Solution
Xenese builds physics-informed digital twins of production lines, integrating PLC/SCADA data and operational KPIs. Scenario simulations run continuously using GenAI to optimize machine sequences and buffer loads.
Key Results
%
increase in daily data throughput
%
increase in daily data throughput
%
reduction in waste reduction
%
reduction in waste reduction
%
reduction in product rework and scrap
%
reduction in product rework and scrap
Automated
Supply Chain
Synchronization
Business Challenge
Fluctuating demand signals, inventory misalignment, and rigid scheduling increase costs and delay deliveries
Xenese™ Solution
Xenese applies real-time transactional machine learning at both the edge and core—ingesting demand signals (orders, forecasts, POS, market data), operational constraints (line status, labor, energy), and supplier variability (delivery ETA, quality flags). Each product line or SKU is modeled as a dynamic entity, enabling continuous micro-adjustments to production rates, sourcing, and logistics in memory, in real time.
Key Results
%
reduction in stockouts
%
reduction in stockouts
%
faster response to demand shifts
%
faster response to demand shifts
%
increase in forecast accuracy
%
increase in forecast accuracy
AI Powered
Quality Control
Business Challenge
Manual visual inspections miss subtle defects and slow throughput. Scaling quality checks without increasing labor remains a challenge.
Xenese™ Solution
Xenese applies computer vision + ML to in-line inspection cameras. Entity-level image models detect micro-defects in coatings, welds, or assemblies. GenAI classifies severity and logs visual anomalies to an immutable ledger for traceability.
Key Results
%
defect detection accuracy
%
defect detection accuracy
%
reduction in inspection cycle times
%
reduction in inspection cycle times
%
reduction in product rework and scrap
%
reduction in product rework and scrap
Digital Twin
Production
Optimization
Business Challenge
Inefficient line configurations and inventory delays cause bottlenecks and material waste. Legacy systems cannot simulate process options in real time.
Xenese™ Solution
Xenese builds physics-informed digital twins of production lines, integrating PLC/SCADA data and operational KPIs. Scenario simulations run continuously using GenAI to optimize machine sequences and buffer loads.
Key Results
%
increase in daily data throughput
%
reduction in waste reduction
%
faster production scenerio testing and validation
Automated
Supply Chain
Synchronization
Business Challenge
Fluctuating demand signals, inventory misalignment, and rigid scheduling increase costs and delay deliveries
Xenese™ Solution
Xenese applies real-time transactional machine learning at both the edge and core—ingesting demand signals (orders, forecasts, POS, market data), operational constraints (line status, labor, energy), and supplier variability (delivery ETA, quality flags). Each product line or SKU is modeled as a dynamic entity, enabling continuous micro-adjustments to production rates, sourcing, and logistics in memory, in real time.
Key Results
%
reduction in stockouts
%
faster response to demand shifts
%
increase in forecast accuracy
AI Powered
Quality Control
Business Challenge
Manual visual inspections miss subtle defects and slow throughput. Scaling quality checks without increasing labor remains a challenge.
Xenese™ Solution
Xenese applies computer vision + ML to in-line inspection cameras. Entity-level image models detect micro-defects in coatings, welds, or assemblies. GenAI classifies severity and logs visual anomalies to an immutable ledger for traceability.
Key Results
%
defect detection accuracy
%
reduction in inspection cycle times
%
reduction in product rework and scrap
Lead What’s Next With Xenese
Join First Genesis and our partners to build Real-Time AI you can trust.
Lead What’s Next With Xenese
Join First Genesis and our partners to build Real-Time AI you can trust.
Lead What’s Next With Xenese
Join First Genesis and our partners to build Real-Time AI you can trust.