Show Cases

Keplore has been used to build and deploy production-grade AI systems across vision inspection, robotics, energy systems, and hardware-constrained environments.

These use cases reflect real-world constraints such as limited data, strict validation requirements, hardware bottlenecks, and multi-environment deployment, beyond lab-scale experimentation.

Case Study

IntelliFlow: Autonomous Embodied Intelligence for Multi-Agent Warehouse Orchestration

IntelliFlow: Autonomous Embodied Intelligence for Multi-Agent Warehouse OrchestrationLive Demo

A real-time orchestration system that autonomously coordinates robots and labor, improving warehouse throughput while adapting to operational changes without manual intervention.

Case Study

RoboOptimize: Agentic Research System for Robotic Component Integrity and Line Efficiency

RoboOptimize: Agentic Research System for Robotic Component Integrity and Line EfficiencyLive Demo

A self-optimizing AI platform that keeps robotic production lines running efficiently by detecting defects, monitoring equipment health, and continuously improving OEE.

Case Study

MedGuard-AI: Visual Inspection for Medical Packaging Integrity and Compliance

MedGuard-AI: Visual Inspection for Medical Packaging Integrity and ComplianceLive Demo

An enterprise-grade vision system that ensures zero-defect pharmaceutical and medical device packaging by detecting seal, label, and structural defects within fully auditable, regulatory-compliant workflows.

Case Study

SunScan-AI: Autonomous Solar Panel Asset Integrity and Electroluminescence Diagnosis

SunScan-AI: Autonomous Solar Panel Asset Integrity and Electroluminescence DiagnosisLive Demo

A high-precision EL-based inspection system that detects and localizes photovoltaic module defects while quantifying energy yield loss for manufacturing and field operations.

Case Study

B-Life-AI: Advanced Battery Prognostics for SOH Estimation and RUL Forecasting

B-Life-AI: Advanced Battery Prognostics for SOH Estimation and RUL ForecastingLive Demo

An intelligent battery health system that predicts State of Health (SOH) and Remaining Useful Life (RUL) from real-time BMS data, enabling proactive maintenance, failure prevention, and warranty optimization.

Case Study

MagVision-AI: Multi-Model Rapid Deployment for Universal Magnet Quality Control

MagVision-AI: Multi-Model Rapid Deployment for Universal Magnet Quality ControlLive Demo

A flexible vision inspection system that supports parallel training of multiple defect models and rapid edge deployment, enabling manufacturers to keep inspection logic aligned with fast-changing production lines.