Build systematic AI capability for predictive maintenance, quality control, supply chain optimization, and generative AI applications: with energy efficiency, ethical AI practices, and measurable ROI built in from day one.
Equipment failures cost manufacturers $50B annually. Reactive maintenance wastes resources; scheduled maintenance is inefficient.
→ Predictive maintenance AI reduces downtime 30-40% with energy-efficient edge computing
Human inspection is slow, inconsistent, and expensive. Defects caught late multiply costs through rework and warranty claims.
→ Computer vision AI detects defects 50x faster with 99.5% accuracy
Demand forecasting errors create costly stockouts or excess inventory. Supply disruptions catch manufacturers unprepared.
→ AI-powered demand forecasting + supply risk prediction improves accuracy 25-35%
Experienced workers retiring take decades of tribal knowledge. Technical documentation is outdated, incomplete, or doesn't exist.
→ Generative AI creates technical docs, training materials, and knowledge bases from existing data
We implement AI systems that create measurable operational improvements and ROI
Machine learning models analyze sensor data from equipment to predict failures before they occur. Our systems integrate with existing SCADA/MES platforms and run on energy-efficient edge devices for real-time predictions.
Vision AI systems inspect products at production speed, detecting defects invisible to human inspectors. Our explainable AI frameworks show exactly why products were flagged, building trust with quality teams and meeting automotive/aerospace audit requirements.
Machine learning models forecast demand, predict supply disruptions, and optimize inventory across your supply network. Our systems integrate market data, weather, geopolitical risk, and internal data for comprehensive supply chain intelligence.
Large language models generate technical documentation, training materials, and standard operating procedures from existing data. Our responsible AI approach ensures accuracy, includes human review workflows, and maintains version control for compliance.
Tier 1 automotive parts manufacturer | 4 plants | 1,200 employees
Critical injection molding equipment experienced unexpected failures causing production delays and millions in lost output. Reactive maintenance was costing $3.2M annually, while scheduled maintenance wasted resources on equipment that didn't need service.
We deployed edge-based predictive maintenance AI analyzing vibration, temperature, and pressure sensors across 47 critical machines. The system predicts failures 2-3 weeks in advance with 94% accuracy, integrating directly into their existing maintenance scheduling system.
"Posvo didn't just install AI software: they built a system that fits our reality. The maintenance team trusts the predictions because they understand how the system works. That trust is what makes this sustainable."
— VP of Manufacturing Operations
We understand OEE, Six Sigma, Lean principles, and the realities of 24/7 production environments. Our AI solutions integrate with existing MES, ERP, and SCADA systems.
Edge computing and optimized models reduce energy costs 40-60% vs. cloud-only solutions. Critical for manufacturing's tight margins and sustainability goals.
Pilot in non-critical areas first. Gradual rollout with kill switches and human oversight. We never compromise production stability for AI innovation.
Start with a strategic conversation about where AI fits in your manufacturing operations, what outcomes matter most, and how to build lasting competitive advantage with responsible AI practices.
Initial consultations are confidential and require no commitment.
A strategic conversation about where organizational intelligence fits in your business, what it should accomplish, and how to build it as lasting capability.