System Architecture

The platform leverages a cutting-edge AI-native stack designed for high-availability and specialized Agentic Workflows:

    • Core Logic & Orchestration: Developed using Python (Flask) and Angular for a responsive full-stack experience.
      LLM Infrastructure: Powered by the Gemma Model running within Ollama containers.
      Vector Search: Utilizes Qdrant as a high-performance VectorDB to enable sophisticated Retrieval-Augmented Generation (RAG) capabilities.
      Deployment & Scaling: Orchestrated via Docker and Kubernetes to ensure a resilient, cloud-native infrastructure.

    • Knowledge Base Content

    The system is optimized to process and retrieve insights across several specialized domains:


    Scientific Testing
    • Technical scientific papers are great for testing structural understanding
      Structural Understanding: Features a selection of technical scientific papers utilized for evaluating the system’s comprehension of complex document layouts.

    • Clinical & Neurological Expertise

    The platform contains extensive data regarding the diagnosis, management, and treatment of various neurological conditions, specifically:

    • Meningiomas: In-depth updates on treatment care, skull base nuances, and surgical recurrence rates.
      Gliomas: Comprehensive guides on symptoms, diagnosis, and treatment protocols for both standard and high-grade cases.
      Pituitary Tumors: Detailed workflows for endoscopic surgery and endocrine management.
      Neuroscience Foundations: Academic resources covering neuroanatomy for clinical pathology and the physiological/psychological aspects of the "Emotional Brain".
      General Oncology: Broad research on tumors of the Central Nervous System.

    • we can get information on the topics listed under Clinical & Neurological Expertise