Mahek Makwana

– Developed an automated DocSync Agent to audit and synchronize technical documentation with source code logic – I engineered the DocSync Agent, an automated AI auditing system designed to eliminate "Documentation Drift" by ensuring technical manuals remain in perfect sync with evolving source code. – Developed a Deterministic NLP Engine: Built a core analysis pipeline using TF-IDF (Term Frequency-Inverse Document Frequency) to weight technical logic and Cosine Similarity to measure the mathematical alignment between code and documentation. – Architected a Multi-Layer System: Designed a robust four-layer architecture—Analysis (AST-based parsing), Orchestration, Generation, and Interface—to handle complex project structures and secure data flow. – Automated Continuous Validation: Integrated the agent into CI/CD pipelines via GitHub Actions, enabling automatic documentation health checks during every code commit. – Engineered for Privacy & Efficiency: Developed a "Privacy-First" local execution model that requires no external cloud APIs, reducing manual review time by 70% and improving documentation coverage by 85%. – Built a Premium Visual Dashboard: Developed an interactive interface using FastAPI and TailwindCSS to provide developers with real-time "Traffic Light" health scores and algorithmic fix suggestions.

– Developed a generative AI that produces realistic data in just seconds or minutes, helping insurance companies simulate customer scenarios. – Incorporated user constraints into the generated datasets, allowing customization of the number of rows, required columns, and more. – Created a user-friendly interface using Streamlit, making it easy for users to interact with the application.

– Applied artificial intelligence techniques in a real-world setting and enhancing understanding of AI's practical applications. – Expertise in preprocessing radiological images, a critical step in preparing data for machine learning model – Learned about the development and application of LLMs for generating medical reports. – Developed a deeper understanding of how AI can improve veterinary diagnostics and contribute to animal welfare. – Built connections with professionals in the AI and veterinary fields, expanding professional network.

– Learned deep dived into AI solutions for CRM – Through in-depth research I gained valuable insights such as lead scoring and chatbots – I Learned how NLP in CRM can analyze customer interactions, extract key insights and improve communication, ultimately strengthening customer relationships.

– In-depth pre processing of extracted data with Power BI – Generate graphics using python – Visualized data in all significant trends such as style, colours, material types, etc