Agentic AI Systems

In Company: Potentiam Ltd

Timeline: Mar 2025 - PRESENT

Work done: Actively researching and prototyping Agentic AI architectures using tools like LangGraph, Google ADK, and Pydantic. The project explores the Google A2A protocol to enable autonomous, multi-agent interactions, currently in its early experimentation phase.

Private Enterprise GPT

In Company: Potentiam Ltd

Timeline: Jan 2025 - Feb 2025

Work done:

• Designed, configured, and deployed an in-house Private GPT system using an open-source GitHub repository.
• The solution was hosted on an Ubuntu Linux server, secured with Nginx reverse proxy and SSL certification, and mapped to a custom domain.
• To ensure resilience and automation, the application was converted into a system service, incorporating log rotation, cron jobs, and auto-restart mechanisms.
• Additionally, the hardware setup was transformed into a remotely accessible server via VNC, allowing seamless monitoring and usage by the entire company.
• This deployment enabled the organization to replace external AI tools like ChatGPT and DeepSeek, ensuring data privacy by keeping all interactions in-house.
• Migrated user authentication system to OAuth with Microsoft Authenticator, restricting access to employees under the company domain.

Skills & Technology Implemented:

• Linux Server Administration (Ubuntu) – System configuration, user management, security hardening.
• DevOps & MLOps – Reverse proxy setup, SSL certification, domain mapping, service automation.
• Hosting & Deployment – CI/CD principles, running application as a service, auto-restart & monitoring.
• Open Source Integration – Customizing an open-source AI model to fit organizational needs.
• Database Management – SQLite configuration and data handling.
• Remote Server Access & Monitoring – VNC setup for remote administration and usage.
• OAuth Integration - Implemented Microsoft Authenticator-based login to allow only company domain users to access the Private GPT platform.

AI Search

In Company: Potentiam Ltd

Timeline: Dec 2024 - Jan 2025

Work done:

• Developed an AI Search widget for the organisation's internal tool to provide smart and quick access to the employee salary data, market salary data, job specs, and skills matrices.
• Enhanced the traditional search bar by integrating an “Ask AI” feature that processes user queries and provides accurate results with source links, cutting user navigation time by 50%.
• Designed and implemented a RAG (Retrieval-Augmented Generation) system, incorporating:
• FAISS for embedding storage and similarity search.
• LangChain to orchestrate document retrieval, query formatting, and response generation using the LLM.
• Optimized embedding algorithms and document-based metadata storage, improving accuracy from 75% to 90% and reducing hallucinations.
• Introduced caching with SQLite to handle repeated queries efficiently, minimizing redundant computation.
• Implemented structured HTML response validation to ensure consistent and interactive UI experience.
• Deployed the production system via IIS, by bundling it into a JavaScript widget for seamless integration into the company’s website.

Skills & Technology Implemented:

• Frontend Development: React.js, TailwindCSS
• Backend Development: Flask (Python), MongoDB (user conversations), SQLite (cache)
• RAG Architecture:
  • Embedding and similarity search: FAISS, PCA for dimensionality reduction
  • LLM: Ollama server with Llama3.x models
  • LangChain for end-to-end pipeline integration
  • Prompt templates and validation with Pydantic and BeautifulSoup
• Deployment: IIS server hosting with optimized domain and site configuration
• Problem-Solving:
• Enhanced embedding accuracy and response speed.
• Reduced hallucinations with document-based metadata storage.
• User-centric improvements validated by a 90% satisfaction rate and 50% time savings.

Intelligence Framework

In Company: Potentiam Ltd

Timeline: Sept 2024 - Dec 2024

Work done:

• Designed and developed an "All-in-One Intelligence Framework" to assist Talent Acquisition and HR teams with candidate evaluation, job specification creation, and data management.
• Features Developed:
• Resume Reviewer: Analyzed candidate resumes against job descriptions, providing strengths, weaknesses, and training suggestions. Results were downloadable and processed for up to 10 candidates simultaneously within 10 seconds.
• General Chatbot: Built an LLM-powered chatbot with a dynamic UI for safe, secure company use. Features included conversational history, responsive design, and well-formatted chat messages.
• Job Spec and Skills Matrix Generator: Created job specifications and skills matrices from job titles, trained strictly on internal company data, with outputs downloadable as Word documents.
• Resume Formatter: Transformed pasted resume content into client-specific templates, ensuring formatting consistency without altering content. Each resume was stored in conversational history for easy reference.
• Job Title Comparison: Enabled role comparison with drop-down menus, generating detailed analyses based on internal databases without internet-based data.
• Boosted the TA team's efficiency by reducing candidate screening time from hours to seconds and reducing the HR team's workload by enabling instant internal data generation.

Skills & Technology Implemented:

• Frontend Development: React.js, JavaScript, HTML, CSS
• Backend Development: Flask (Python), MongoDB (storing user conversations)
• AI Architecture:
• LLMs: Ollama server for local LLM hosting and processing
• LangChain: For context handling, prompt templates, and conversational workflows
• Problem-Solving:
• Delivered fast (2-3 seconds) and accurate conversational AI responses.
• Streamlined manual HR processes, significantly improving efficiency and reducing human errors.
• Designed user-friendly and responsive UIs for seamless interaction and data download.

Chatbot Development

In Company: Potentiam Ltd

Timeline: Jan 2024 - Sept 2024

Work done:

• Spearheaded the development of an intelligent chatbot for Potentiam Ltd as a widget, leveraging an in-house trained Small Language Model (SLM) with internal company data.
• Migrated the chatbot from Rasa Open Source to Rasa Pro CALM, enabling advanced conversational AI with fallback handling and seamless context-switching.
• Redesigned and developed a fully customized UI, integrating key functionalities:
• File Downloads: Generating and downloading formatted Word and PDF outputs.
• Speech-to-Text (STT): Allowing voice-based interaction.
• Conversational Features: Enhanced handling of interruptions and context switching for smoother user interactions.
• Developed custom actions (python functions) for data preparation, database setup, and Rasa integration for efficient data retrieval.
• Overcame significant technical challenges:
• Installation Issues: Resolved package version conflicts through custom debugging and testing multiple environments.
• UI Limitations: Replaced default Rasa UI with an alternative Flask-based solution, implementing missing functionalities and extending JavaScript features.
• Enhanced chatbot intelligence by integrating LLMs (Ollama) for fallback responses when queries exceeded SLM's knowledge base, ensuring continuous and relevant interactions.
• Demonstrated expertise in Natural Language Processing (NLP), Natural Language Understanding (NLU) through Entity and Intent recognition, and LLM tooling through the project's architecture.

Skills & Technology Implemented:

• Full Stack Development:
• Frontend: HTML, CSS, JavaScript (Open source widget, later migrated to in-house UI developed using React.js)
• Backend: Flask (API calls), MongoDB (knowledge base)
• AI Architecture:
• Rasa: Migrated from Open Source to Rasa Pro CALM
• LLM Tooling: Integrated LLMs (Ollama) for fallback scenarios
• Problem-Solving:
• Debugged installation issues, implemented custom solutions for data retrieval, and improved conversational design.
• Designed scalable systems for handling diverse and dynamic data inputs without compromising response times.

This project served as a pilot for demonstrating AI's potential in business workflows, blending innovative AI architecture with practical, user-centric design.

Organisation Chart Generator

In Company: Potentiam Ltd

Timeline: Jun 2024 - Jul 2024

Work done: Developed two key applications designed to automate and visualize organizational hierarchy efficiently:

• Excel Generator:
• Utilized an in-house Automated Web Scraping tool to extract relevant data and organize it into a downloadable Excel sheet.
• The tool was containerized using Docker, ensuring seamless deployment and scalability.
• UI Development was achieved with Flask and Python, offering a user-friendly interface for data extraction and download.
• Technologies used: Beautiful Soup, ChromeDriver, Docker.
• Chart Generator:
• Took the preprocessed Excel file from the Excel Generator as input.
• Produced high-quality hierarchy graphs in PNG format for download.
• Built using the Graphviz Python library for graph visualization.
• Hosted as a secure site on the company's IIS server, ensuring accessibility within the corporate domain.
• Technologies used: Flask, Python, Graphviz, IIS Hosting.

This project enabled Sales and Marketing teams to generate organizational charts in under 15 seconds, vastly improving efficiency. The tool quickly became the most utilized resource for these teams and remains under continuous development to handle the latest package updates and maintain compliance with web security standards.

Skills & Technology Implemented:

• Frontend and Backend Development: Flask, Python, HTML, CSS, MongoDB (User login detials)
• Data Processing and Visualization: Beautiful Soup, ChromeDriver, Graphviz
• DevOps: Docker for containerization, IIS Hosting
• Problem-Solving: Boosted operational efficiency, automation of data processing, and integration of secure deployment practices

Q&A system over documents

In Company: Wipro Ltd

Timeline: May 2023 - June 2023

Tech Stacks: LangChain | Streamlit | ChatGPT API

Fine-tuned LLMs using LangChain and implemented a simple Q&A system over documents, optimizing its accuracy, and created an interface using Streamlit. This work enabled users to have interactive and informative conversations while effortlessly extracting valuable insights from large volumes of textual data.

Internship Mentor

In Company: Potentiam Ltd

Timeline: Sept 2024 - Nov 2024 (8 weeks)

Skills and Techs: Python | Libraries- Tensorflow, Keras, OpenCV | Computer Vision | Project Management | Mentorship | Communication | Technical Assistance

Mentored a pre-final year AI/ML Student intern on a Live Video based Face Mask Detector project. The system leveraged OpenCV for video stream processing along with TensorFlow and Keras libraries for mask detection, based on Haar Cascade Classifier which was trained in-house using the raw data provided.

Web Applications Development

In Company: Potentiam Ltd

Timeline: Dec 2023 - Present

Skills and Techs: Project Management | Team Communication | Stakeholder requirments | Data processing | Full Stack: Angular, RESTful APIs, MySQL

Led the coordination between management and development teams for two different web applications tailored for internal staff as well as the clients. Oversaw client requirement gathering, workflow design, data management, and testing phases.

Cybersecurity Audit

In Company: Potentiam Ltd

Timeline: Nov 2023 - Jan 2024

Skills and Techs: Cybersecurity Assessment | Vulnerability Identification | Antivirus Management | Operating System Security | Network Configuration Analysis | User and Registry Management | Techs: Qualys, Windows Firewall, Windows OS Tools including lusrmgr (Local Users and Groups) and Registry Editor

As part of a comprehensive cybersecurity audit within my organization, I actively participated in evaluating IT operations and assessing the effectiveness of cybersecurity measures. My responsibilities included conducting thorough checks on firewall configurations, antivirus software, and internal operating system settings. Utilizing tools such as Qualys, I identified vulnerabilities and implemented resolutions to enhance the security posture of the organization.

Additionally, I performed in-depth analyses of network settings and utilized Windows Local User and Group Management (lusrmgr) alongside the Registry Editor to ensure compliance with security policies and best practices.

Power BI Dashboards

In Company: Potentiam Ltd

Timeline: Oct 2023 - Dec 2023

Skills and Techs: PowerBI | Data Preprocessing | Data Analysis

Developed Dashboards using PowerBI which provided an in-depth and smart overview of data for the Finance, Sales and Marketing teams respectively.