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Schedule Interview NowMy name is Aniket K. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: AI Agent Development, Artificial Intelligence, Dialogflow API, Data Science, Retrieval Augmented Generation, etc.. I hold a degree in Bachelor of Technology (BTech). Some of the notable projects I’ve worked on include: Build an LLM and RAG-based Chat Application with AlloyDB and Vertex AI, Multi-Agent system using ADK, A2A, MCP on Google Cloud with Vertex AI, Predict Visitor Purchases with a Classification Model in BigQuery ML, AI Telephony Voice Assistant (Low Latency + Multi Language), A.I Chatbot on Phone Calls, etc.. I am based in Gaya, India. I've successfully completed 21 projects while developing at Softaims.
I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.
I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.
My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.
Main technologies
2 years
1 Year
1 Year
1 Year
Potentially possible
Google India
This project demonstrates how to enhance large language model (LLM) responses using Retrieval-Augmented Generation (RAG). By integrating AlloyDB for semantic search of vector embeddings and Vertex AI’s Gemini Pro model, the system retrieves and injects relevant data into prompts, improving LLM accuracy and relevance. The goal is to build a scalable, intelligent application that understands natural language queries and delivers precise, context-rich answers.
I have built an AI-powered social planning prototype using multi-agent architecture on Google Cloud (Vertex AI, Cloud Run, Spanner). Leveraged Gemini LLMs, ADK, A2A protocol, and MCP to automate user profiling, event discovery, and platform interaction. Improved user engagement and event coordination by orchestrating intelligent agents for social listening and personalized suggestions.
The goal of this project was to predict which first-time ecommerce visitors would return and make a purchase. Using BigQuery ML, I built and trained logistic regression models on user session data. Starting with basic features like bounce rate and time on site, I later improved the model through advanced feature engineering, including traffic source, device type, and checkout progress. This increased model accuracy (ROC AUC from 0.72 to 0.91), enabling more targeted marketing and higher conversion rates.
Discover the revolutionary AI Telephony Voice Assistant: a multi-industry solution designed to elevate customer support. This assistant proficiently handles phone calls, providing accurate, low-latency assistance across a vast knowledge base (MySQL database & RAG). It converses naturally in multiple languages, powered by OpenAI, Eleven Labs, and Twilio, with a Python/FastAPI backend deployed on OVH Server. This aim of project is to give you experience to unparalleled efficiency and customer satisfaction with this expertly developed and deployed solution.
Designed an AI chatbot on Dialogflow integrated with Twilio for voice and messaging services. Deployed a Python-based FastAPI server with real-time communication protocols including WebSocket, WebRTC, and gRPC to reduce latency and enhance response time.
Bachelor of Technology (BTech) in