Company Projects 

Developed and maintained application modules for Classes 9th–12th, including Main Form, Late Fee Form, and Edit Application Form

Contributed to the Result Module, ensuring accurate data processing and seamless result display

Implemented AI-based face validation to verify student photo uploads and prevent incorrect or mismatched images

Developed AI-driven document validation to detect blank, blurred, or unreadable images/PDFs, improving data quality and reducing manual verification

Applied validation checks to ensure uploaded documents meet clarity and readability standards

Performed bug fixing, data validation, and performance optimization to maintain system stability

Designed and optimized SQL queries and stored procedures for efficient data handling

Collaborated with cross-functional teams for requirement analysis, testing, and timely delivery

Developed and maintained core modules including Application Form, Edit Application, Document Verification, and Objection Management

Implemented vacancy collection system across multiple administrative levels (State, District, Block, CDPO, DPO)

Contributed to Pre-Provisional and Final Merit List generation for Worker and Helper posts

Designed and deployed an AI-powered chatbot using n8n workflows and LLM APIs, integrated with the Chayan Portal to automate user query handling

Worked on AI-driven automation workflows to streamline repetitive processes and reduce manual effort

Performed data validation, bug fixing, and performance optimization to ensure stable and accurate functionality

Supported Objection Calling & Verification modules, ensuring smooth workflow and correct data processing

Developed and optimized SQL queries and stored procedures for efficient data operations

Actively participated in UAT, functional testing, and system stabilization

Designed and implemented an end-to-end AI pipeline to extract structured data from handwritten school registers using OCR and image processing techniques

Utilized EasyOCR/Tesseract for handwritten text recognition and applied preprocessing techniques (noise removal, image enhancement)

Built a data post-processing module to map unstructured OCR output into structured tabular format

Developed a scalable backend system to store extracted data into SQL Server with validation and error handling

Created an interactive UI to visualize extracted data in grid format and implemented Excel export functionality

Reduced manual data entry effort by automating digitization of handwritten records and improved operational efficiency

Designed Power BI dashboards to visualize MPPSC application trends, objection resolution rates, and refund analytics, improving decision-making by 20%

Optimized SQL queries to process 100,000+ candidate records for application workflows, result generation, and refund validations

Worked on Application, Edit, and Court Case modules, implementing dynamic business logic based on government rules

Automated admit card and call letter generation using ASP.NET MVC and SQL Server

Streamlined objection handling and refund processes, reducing processing time by 15%

Conducted security audits implementing DoS protection, CAPTCHA, and input validation

Built an AI-powered system to extract and process data from handwritten registers and 60-page PDF rulebooks using OCR and LLM techniques

Designed end-to-end pipeline to convert unstructured PDF data into structured format for form generation

Automated requirement extraction from rulebooks and developed structured grid UI with Excel export

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