Hi, I’m Srikanth, a passionate and versatile developer with hands-on experience across a wide range of technologies. I specialize in building robust solutions in Web Development, Machine Learning, Artificial Intelligence, Database Design, and Embedded Systems.
Over the years, I have worked on various impactful projects, including:
Web Applications & APIs
Proficient in building scalable websites and backend APIs using Django, Flask, and modern frontend frameworks. I’ve developed platforms ranging from SaaS tools to custom dashboards.
Database Design & Management
Strong experience in designing, managing, and optimizing databases using SQL, MySQL, PostgreSQL, and SQLite. I’ve also worked on Text-to-SQL AI systems, automated querying, and backend database integrations.
Machine Learning & AI Solutions
Skilled in computer vision, deep learning, and automation, I’ve worked on projects like object detection, defect detection in manufacturing, OCR systems, intelligent chatbots, and AI-driven automation, utilizing models like YOLO, PaddleOCR, and Gemini APIs.
Deployment & DevOps
Experienced in deploying applications on Linux servers, cloud instances, and handling Docker, systemd services, API hosting, and backend server management.
Embedded AI on Edge Devices
Hands-on with deploying AI models on embedded systems like RKNN, NanoPi, and ARM-based edge devices, optimizing models for real-time performance.
Automation & Custom Tools
Built automation scripts, data extraction tools, and AI-powered bots to simplify and accelerate workflows.
💼 Tech Stack & Skills:
Languages: Python, JavaScript, Bash, SQL, C, C++
Frameworks: Django, Flask, FastAPI, Tailwind, React (basic)
Databases: MySQL, PostgreSQL, SQLite, SQL-based automation, Text-to-SQL AI systems
AI/ML: YOLO (v8), RKNN, PaddleOCR, OpenCV, TensorFlow, PyTorch
Deployment: Linux servers, Docker, systemd services, API hosting
Edge AI: RKNN Toolkit, embedded AI on ARM devices (e.g., NanoPi, RK boards)
Others: Automation, scripting, API development, chatbot development with Gemini API
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Industry Experience
🔧 Printing Shop :
*Developed a full-stack document printing platform connecting students with nearby shopkeepers
*Built with React.js (frontend), Node.js/Express (backend), and PostgreSQL (database)
*Integrated Firebase Storage for secure document upload and retrieval
*Implemented JWT-based authentication with separate access control for students and shopkeepers
*Designed dynamic shop availability status using checkbox (activity column) to enable/disable order access
*Integrated PDF viewer for document previews, disabling download to preserve content privacy
*Limited shopkeepers to maximum 3 clicks per document link, preventing overuse or downloads
*Enabled password protection on downloaded PDFs for security
*Designed order management dashboard for shopkeepers with status toggles: “Processing” ↔ “Completed”
*Prioritized teacher orders using optimized SQL queries based on a separate teachers table
*Enabled students to choose print options like soft binding and make payments through integrated gateway
*Built Intelligent Error Detection system to catch:
*Low resolution files
*Unsupported formats
*Incorrect document sizes
*Integrated ARIMA-based demand forecasting on shopkeeper insights page to predict high-demand periods
*Ensured navigation control on the “Thank You” page, preventing backward access
*Deployed the platform using Render for both frontend and backend
🔹Project Overview:
Developed an advanced AI-powered chatbot capable of answering questions based on both documents (like PDFs) and structured databases. The chatbot was integrated with natural language processing (NLP) models and Text-to-SQL capabilities, enabling users to interact with data conversationally.
🤖 AI Chatbot with Document & Database Querying:
*Conversational interface powered by Gemini API and custom AI models.
*Users could ask natural language questions, and the bot converted them into SQL queries in real-time.
*Supported fetching insights from both documents (PDFs) and SQL databases.
🗄️ Database Management & Optimization:
*Renamed and refactored tables and columns for improved clarity and maintainability.
*Implemented table partitioning based on date, category, or region for faster query performance.
*Added indexes on high-usage columns, significantly improving data retrieval speeds.
*Performed query optimization to handle large datasets efficiently during real-time chatbot interactions.
*Managed database migrations, ensuring smooth updates and structural changes.
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