Ghufran Barcha

Developed a Python-based FastAPI application to automate OT cybersecurity risk assessment. The API processes asset data (Excel) and vulnerability scans (PDF), enriching CVE information via the NVD API. It employs a hybrid approach: initial rule-based severity assignment followed by LLM refinement using Langchain with the Deepseek model via Groq. This provides nuanced risk levels and detailed justifications based on OT context (criticality, safety, isolation). The system outputs structured JSON results, streamlining vulnerability management in industrial environments.
Technologies: Python, FastAPI, Pandas, Pymupdf, Langchain, Groq API (Deepseek), NVD API.

This project is an AI-powered medical intake and clinical summary generator that automates patient data collection and report creation. The frontend, built with React, provides an intuitive interface for patients or clinicians to input information such as symptoms, medical history, and demographics. Once submitted, the data is processed through an n8n workflow integrated with OpenAI GPT models and LangChain, which analyze the input, generate a structured medical summary, and convert it into a professional PDF report for download or storage.

Tools Used:
N8N, React, OpenAI, Postgres