PGR provides a cyber‑physical system platform that ingests sensor, camera, and production data from existing manufacturing equipment and applies proprietary graph‑analysis, AI, and quantum‑ready algorithms to simulate, optimize, and automatically adjust processes in real time. The solution runs on a hybrid classical‑quantum compute framework, delivering continuous predictive insights, hands‑free equipment tuning, and rapid implementation without requiring new hardware, helping manufacturers cut operational costs and improve efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often rely on fragmented data sources, manual process studies, and costly hardware upgrades to improve factory efficiency, leading to lengthy implementation cycles and limited real‑time insight into operations.
Solution
PGR offers a cyber‑physical system (CPS) platform that ingests sensor, camera, and production data from existing equipment and IT systems, then applies proprietary graph‑analysis, AI, and quantum‑ready algorithms to simulate, optimize, and automatically adjust processes in real time. The solution runs on a hybrid classical‑quantum compute framework, delivering rapid, data‑driven recommendations and hands‑free adjustments without requiring new hardware. By continuously learning from past performance, the platform provides predictive analytics, inventory and tool tracking, and employee performance feedback, enabling factories to reduce operational costs, shorten implementation time to weeks, and sustain ongoing efficiency gains.
Target Audience
Primary customers are mid‑size to large manufacturers in sectors such as aerospace, automotive, and high‑mix production that need real‑time optimization of assembly lines, inventory, quality assurance, and workforce performance.
Features
- Real‑time data capture using high‑resolution cameras and IoT sensors with proprietary OCR to digitize physical processes
- Graph‑based modeling of machines, people, and materials that runs on quantum‑accelerated simulations for optimal configuration discovery
- AI‑driven, hands‑free adjustments that automatically fine‑tune schedules, resource allocation, and equipment settings
- Continuous machine‑learning loop delivering predictive insights, root‑cause analysis, and progressive performance improvements
- Integrated view across enterprise tiers (operator, team, plant, corporate) for coordinated decision‑making
- Hybrid classical‑quantum computing architecture that achieves high‑speed processing without expensive hardware upgrades
- Scalable deployment on‑premises or in hybrid cloud environments, supporting thousands of concurrent users