---
title: "Yeshee Agarwala - AIML - Project Executive in Pune District | Tal"
description: "Meet Yeshee Agarwala, Student | TPO Co-ordinator at DY Patil University based in Pune District. AI stack includes deepmind, hugging face, and langchain. Explore public work links including github."
image: "https://tal.club/meet/yeshee-agarwala/share-image"
---

# Yeshee Agarwala on Tal

## Headline

Student \| TPO Co\-ordinator at DY Patil University

## About

Proficient at thinking out\-of\-the\-box and applying Data Science &amp; AI/ML algorithms to application areas, like Business, Finance, Nutrition, Semiconductors\. Strongly aligned with industry and business requirements and have work experience with technology leaders\. I have a keen interest in problem solving and fields that demand us to apply our logical mind to reach a solution\. I also have an interest in research work and diving deep into mind boggling topics that still appear incomprehensible even today\.

## Location

Pune District

## AI stack

deepmind

hugging face

langchain

langgraph

langsmith

mcp

openai

## Work experience

AIML \- Project Executive at Silicon Interfaces, Navi Mumbai, Implemented Agent B2Cie™ \(B2Cie\.com\) as a multi\-modal, multi\-lingual AI Education Agent with RAG architecture, integrated to communications gateways and workflow integration with shared memory interface and connectors to HRO Agent\. • Responsible to develop:– RAG Modules– Course Materials in Statistics, Linear Programming, Models, Generative AI, and Python– Tutoring AI/ML to HNIs and Corporates in USA and India

Generative AI \- Intern at L&amp;T Technology Services, Jun 2025 \- Dec 2025 · 7 mos, Mumbai, Maharashtra, India, • Engineered 7\+ Generative AI and Agentic AI workflows for enterprise teams across 3 business units, automating data extraction, document understanding, and multi\-step decision\-making processes \. • Designed a Smart AI Data Extraction System using LLMs, LangChain, and FastAPI, achieving 92% structured\-extraction accuracy on large volumes of unstructured financial and operational documents; adopted as the base architecture for an enterprise\-scale internal product and presented to the Nordic Region Head • Built end\-to\-end Agentic AI pipelines for automated document understanding across regulated\-industry workflows, reducing manual review overhead and improving reliability of downstream decision\-making • Designed controlled experiments benchmarking LLM output quality across structured vs\. unstructured inputs at scale, applying systematic debugging to validate statistically reliable accuracy thresholds before production rollout

AIML\- Intern at Silicon Interfaces, Jun 2024 \- Aug 2024 · 3 mos, Mumbai, Maharashtra, India, Built an LSTM sequence model on structured financial time\-series data, reducing multi\-step forecasting error by 18% over a baseline moving\-average model, benchmarking RMSE and MAE \. • Designed a neural network to classify stuck\-at faults from injected semiconductor test vectors, achieving 90%\+ fault\-classification accuracy and contributing to a published research paper • Identified optimal hyperparameter configurations by systematically testing ReLU/Sigmoid activations and RMSProp/Adam optimizers across 10\+ configurations, generating structured experimental reports for senior researchers and engineering leads

## Education

DY Patil University pune

Higher Secondary, Science, Don Bosco school Guwahati

## Public links

- github: https://github\.com/Yeshee\-30

[View the original profile](https://tal.club/meet/yeshee-agarwala)

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