Pavithra Krishnan

RPA Developer with 1+ year of hands-on experience in designing, developing, and implementing intelligent automation solutions using UiPath, n8n, Python, and FastAPI. Experienced in building interactive Power BI dashboards for Sales, Finance, and HR analytics using live production data, with expertise in DAX, Power Query, data modeling, drill-through reports, and interactive visualizations. Skilled in OCR, web, email, and Outlook automation to streamline business processes and improve operational efficiency.

Proficient in developing AI-powered automation solutions using Retrieval-Augmented Generation (RAG), Agentic AI, OpenAI, Ollama, and FastAPI for intelligent query processing. Strong understanding of REST APIs, SQL, workflow automation, and business process optimization, with a passion for delivering scalable, data-driven solutions that enhance productivity and support informed decision-making.

RPA Developer - RND OptimizAR - Coimbatore

(2025-01)

• Designed and deployed end-to-end RPA workflows using UiPath and n8n, automating business processes across web, desktop, and email platforms.
• Built interactive Power BI dashboards — Sales Dashboard, Finance Analysis Dashboard, and HR Analysis Dashboard — connected to live production data.
• Wrote advanced DAX queries to compute KPIs, dynamic measures, and calculated columns for real-time business reporting.
• Implemented drill-through navigation and slicers in Power BI reports, enabling stakeholders to explore granular data insights interactively.
• Developed OCR-based document processing pipelines and AI-driven content generation workflows integrated within web applications.
• Automated Outlook email extraction and structured data storage into Excel reports, reducing manual processing time significantly.
• Collaborated with cross-functional teams to gather requirements, document processes, and deliver scalable automation and analytics solutions.
• Built Nexusopt, an agentic AI system using the Strands Agentic AI framework and Retrieval-Augmented Generation (RAG) with Ollama and OpenAI models to process natural language queries related to attendance and leave management.
• Designed intent-based tool-selection logic to dynamically route user queries — such as leave-type requests — to the appropriate tool (e.g., leave_tools, attendance_decision_tool) and retrieve accurate responses from the database.
• Applied prompt engineering techniques to improve query interpretation accuracy and response relevance within the RAG pipeline.
• Built and integrated backend services using Python and FastAPI with a MySQL database to support real-time query processing and response generation.

B.Sc. - Computer Science with Data Analytics - Kongunadu Arts and Science College (2022-01 - 2025-12)