Tejasb11802/shiftsense-ai

Shiftsense-AI is an early-stage prototype (0 stars, 0 days old) that implements a 3-agent workflow pattern for industrial troubleshooting. While the concept of using LLMs for 'shift intelligence' is high-value, the project currently lacks the 'data gravity' required for industrial defensibility—such as connectors for PI System, Ignition, or SAP PM. It explicitly models itself after Cognite's Atlas AI, making it a functional clone of existing enterprise patterns rather than a novel breakthrough. The use of LangGraph provides a modern agentic structure, but without proprietary fine-tuned models for sensor data interpretation or a massive library of historical failure modes, it remains a commodity wrapper. The primary threat comes from industrial platform giants (AWS IoT, Azure Digital Twins) and incumbents (Cognite, C3.ai) who already possess the underlying data silos and are rapidly layering similar agentic interfaces on top. Given the 0-star traction, it currently represents a personal experiment or educational repo rather than a defensible product.