video1.0<iframe src="https://www.loom.com/embed/d24b08c8d1f448fc95192203f3230c3a" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/d24b08c8d1f448fc95192203f3230c3a-5659d5a70153be84.gif888.912In my Loom, I demo Study Mind AI, a RAG-powered study assistant built to improve reliability and prevent hallucinations by grounding every answer in a student’s own notes. I built it with Python, GPT 4.1 mini, Chroma, and local sentence transformers, and added guardrails plus an automated evaluation harness. The pipeline is guardrails, then a StudyMind agent that classifies the task, retrieves top four chunks, generates an answer, and self-verifies with a confidence score and reasoning trace. I also ran 27 guardrail and test chunk cases, 11 predefined harness test cases, and showed prompt injection being blocked. No action was requested from viewers.