Unleash On-Prem AI: A Sovereign Copilot for SAP ECC & S/4HANA

Oxmaint extracts 3+ years of SAP PM work order history, failure records, and maintenance costs, then trains asset-specific failure prediction models on your NVIDIA DGX hardware. These models correlate your historical failure patterns with real-time sensor data (vibration, temperature, pressure, motor current) to predict equipment failures 2–8 weeks before they occur. Predictions automatically trigger SAP PM maintenance orders and SAP MM spare parts procurement — not generic alerts, but structured work orders with correct task lists, materials, and cost assignments.

It depends on your scale. DGX Spark (from $4,699) handles up to 500 assets across 1–2 sites — ideal for SMEs and single-plant operations. DGX B200 ($300K–$500K) serves 500–10,000 assets across 2–10 sites for mid-large enterprise. DGX SuperPOD provides rack-scale AI for 50,000+ assets across 50+ global sites. AI vision inspection runs on NVIDIA Jetson or L4 GPUs at the edge. We also fully deploy on AWS EC2, Azure ND, or GCP A3 instances within your VPC for hybrid scenarios.

Yes. Technicians describe a problem in plain English — for example, "Compressor C-14 is making a grinding noise and running hot." The AI copilot creates a structured SAP PM work order with the correct equipment number, failure code, task list, estimated materials from SAP MM, priority classification, and technician assignment. This reduces work order creation time by 60% and eliminates manual data entry errors. The copilot inherits SAP authorization objects, so technicians only access equipment they're assigned to.

Yes. Oxmaint supports existing IP cameras via ONVIF and RTSP protocols, industrial thermal cameras (FLIR), and machine vision systems from Cognex, Keyence, and Basler. Edge AI inference runs locally on NVIDIA Jetson hardware — sub-100ms detection speed, no cloud required. Every inspection finding is automatically logged in SAP PM with annotated evidence images, severity classification, and recommended corrective actions.

Yes. The entire Oxmaint stack — DGX hardware, NeMo models, RAPIDS analytics, NIM inference engine, and SAP PM/MM/EHS connectors — runs fully offline with zero external API calls. This is specifically designed for defense installations, classified government facilities, pharmaceutical manufacturing, and regulated industries requiring complete network isolation. FIPS 140-2 compliant deployment available.

Full platform deployment including hardware installation, SAP PM/MM/EHS connector configuration, predictive model training on your asset data, AI vision station setup, and technician onboarding: 8–12 weeks. AI vision inspection stations for specific equipment lines can be live in as little as 14 days. The turnkey package includes ongoing support, quarterly model retraining as new failure patterns emerge, and continuous performance monitoring.

Oxmaint's AI predicts spare parts demand based on equipment failure forecasts and SAP PM maintenance history. It dynamically adjusts safety stock levels, auto-raises SAP MM purchase orders when stock drops below calculated thresholds, and prevents both stockouts during critical failures and excess inventory write-offs. In pilot deployments, this reduced spare parts inventory by 28% while maintaining zero stockouts on critical components.

GDPR, HIPAA, EU AI Act (August 2026), FDA 21 CFR Part 11, ISO 27001, ISO 45001 (Occupational Safety), ISO 14001 (Environmental), SOC 2 Type II, DORA, FIPS 140-2, JCAHO (Healthcare accreditation), and OSHA. Oxmaint AI agents continuously scan SAP PM, EHS, and sensor data to auto-generate audit trails, compliance documentation, permit-to-work validations, and regulatory reports — turning weeks of manual preparation into hours.