LogiSentinel: Enterprise Fleet Diagnostics AI

In commercial logistics, fleet downtime costs companies millions. While AI can accelerate diagnostics by parsing complex 600-page OEM manuals, it introduces a massive enterprise security flaw. Controllers and mechanics naturally include sensitive PII (driver names, phone numbers, exact breakdown locations) in their field reports. Sending this raw data directly to third-party cloud LLMs violates strict corporate privacy laws. LogiSentinel solves this by acting as a highly secure, enterprise-grade intermediary. Built as a decoupled RAG (Retrieval-Augmented Generation) proxy, the user interface never communicates directly with the AI model. Instead, every prompt routes through a custom Python/FastAPI backend. Here, a "Privacy Shield" active regex engine intercepts the payload, automatically scrubbing sensitive data before the request ever reaches Google Gemini. The system grounds itself exclusively on the active vehicle manual, diagnosing the breakdown and generating a precise parts-and-tool list. This allows dispatchers to pre-prep the garage before the truck even arrives. With LogiSentinel, logistics companies achieve faster turnaround times and proactive predictive maintenance, while maintaining 100% control over their enterprise data governance.