Mehedi Hasan Nipu.

Built a Control Set builder that converts any regulatory standard, including GAMP 5, ISO, FDA, and internal SOPs, into a machine-readable clause index using quality-scored PDF/DOCX extraction and parallel Claude Agent SDK workers.

Engineered a clause-by-clause compliance checker where a scoping agent bounds document responsibility and concurrency-capped agents return evidence-cited verdicts with Critical, Major, and Minor severity grading.

Designed the pipeline for resilience with per-slice checkpointing to Azure Blob Storage for resumable retries, citation verification against source files, and deterministic Python-based compliance scoring.

Delivered a grounded chat interface for instant, cited Q&A over each Control Set, plus a unified activity and cost dashboard tracking agent spend and status in Azure SQL.

Developed a SAM.gov scraper and multi-portal aggregation pipeline to automatically discover ServiceNow and ITSM opportunities across US federal and SLED procurement portals, with keyword-based relevance scoring and structured Excel output.

Integrated Azure Document Intelligence and GPT-4.1 to analyze RFP documents, extract structured requirements, and enable natural-language Q&A over indexed document sections stored in Azure SQL.

Developed Claude Agent SDK-powered agents for automated company profiling and end-to-end DOCX and PPTX proposal generation tailored to specific RFP requirements.

Built a unified activity logging and cost analysis dashboard tracking user interactions, agent invocations, document operations, and real-time API spend across Anthropic Claude and Azure OpenAI, with full audit trails in Azure SQL.

Developed a multi-agent orchestration system using Claude Agent SDK to analyze PRD documents and generate implementation plans by discovering reusable components in Azure Blob Storage.

Engineered an automated code-generation pipeline with BackendBuilderAgent creating validated FastAPI applications and FrontendBuilderAgent scaffolding React and Vite projects with npm management.

Implemented a skill-generation system that extracts reusable patterns from GitHub repositories or code archives, generates documentation, and updates the component library.

Built an interactive natural-language CLI for conversational project modification and debugging with automatic port management and session persistence.

Architected an asynchronous FastAPI backend with Azure Blob Storage, multi-format document parsing for PDF, DOCX, and Markdown, and Pydantic validation.

Created Salesforce Apex classes to handle POST and GET operations and enable natural-language interaction with Salesforce data.

Developed custom authentication functions to securely connect Apex classes and manage efficient API communication.

Integrated an Azure AI Foundry Agent to automate Salesforce workflows from natural-language instructions.

Developed text and speech-to-text FastAPI services using Azure OpenAI Whisper for accurate audio transcription.

Built an intuitive multimodal frontend for text and audio operations with an automatic agentic flow.

Developed an AI-based check fraud detection system using advanced machine-learning techniques to identify fraudulent checks.

Leveraged Azure Document Intelligence and the prebuilt US Bank Check model to validate critical check components.

Trained a Siamese neural network for matching signatures against reference and blacklist samples.

Designed a three-level review classification categorizing check images as Safe, Suspicious, or Fraud.

Developed a responsive geographic analysis application using Next.js, React, and shadcn/ui for coordinate and compliance workflows.

Integrated real-time geographic tracking with Leaflet.js maps for dynamic coordinate visualization.

Implemented coverage-analysis tools using the Haversine formula for accurate distance calculation.

Designed a responsive UI system optimized for desktop, tablet, and mobile devices.

Developed a vectorization and storage pipeline for unstructured JSON data using OpenAI embeddings and ChromaDB for fast retrieval.

Implemented RAG-based agents combining vector retrieval and external web search for dynamic chatbot responses.

Designed multi-source knowledge refinement to improve response relevance and accuracy in real time.

Evaluated embedding models with RAGAS to select the most effective model for the target workload.

Developed an AI-powered competitive-analysis system for extracting company services and identifying competitors through web scraping and OpenAI models.

Built a comprehensive SWOT workflow using dynamic AI responses grounded in company and competitor web content.

Integrated extraction, analysis, and report generation to deliver structured insights into market positioning and the competitive landscape.

Developed a Flask-based contract-generation application using AI and OCR to extract, refine, and generate legal document text.

Integrated Groq and LLaMA Vision for accurate processing of complex legal text and images.

Incorporated OCR document processing for digitizing scanned and image-based legal contracts.