TriadInspect AI

Overview: TriadInspect AI is an AMD-powered industrial inspection copilot designed to help factory teams identify potential equipment issues by combining machine images, sensor readings, and technical manuals in one workflow. Problem Statement: Industrial maintenance teams often analyze visual inspections, temperature and vibration readings, and equipment manuals separately. This can make it difficult to detect inconsistencies, verify potential faults, and prepare maintenance reports efficiently. Proposed Solution: TriadInspect AI cmbines these evidence sources to support more informed maintenance decisions. An AI model running on AMD-powered infrastructure analyzes the available information, while a rule-based verification engine checks sensor values against documented thresholds and highlights missing or conflicting evidence. Key Features: 1. Machine inspection using available visual evidence. 2. Sensor monitoring for readings such as temperature and vibration. 3. Technical manual and maintenance checklist analysis. 4. Rule-based validation of numerical thresholds. 5. Inspection statuses: Monitor, Inspect, and Escalate. 6. Maintenance work-order drafts and downloadable reports. 7. Transparent findings that support human review. Technology Stack: Python, Streamlit, AMD-powered AI inference, Pandas, Plotly, and document-processing tools. Expected Impact: TriadInspect AI aims to simplify industrial inspection workflows, improve the traceability of findings, and reduce the effort required to prepare maintenance reports. It combines AI analysis with deterministic checks to make recommendations more transparent. The prototype will be tested using normal, abnormal, incomplete, and conflicting evidence scenarios. It is designed to assist maintenance teams, not replace expert judgment or certified safety inspections.