---
title: "Vanshika Uttarwar - Data Scientist in Bengaluru | Tal"
description: "Meet Vanshika Uttarwar, Data Scientist | Generative AI | LLMs | AI Agents | Python | LangGraph | FastAPI | AWS | Healthcare AI based in Bengaluru. AI stack includes antigravity, claude code, and elevenlabs. Explore public work links including github, medium, and ds-portfolio-sepia.vercel.app."
image: "https://tal.club/meet/vanshika-uttarwar/share-image"
---

# Vanshika Uttarwar on Tal

## Headline

Data Scientist \| Generative AI \| LLMs \| AI Agents \| Python \| LangGraph \| FastAPI \| AWS \| Healthcare AI

## About

Hello\! I’m vanshika, Completed my engineering from Pune university\. I am an AI Engineer with experience building AI\-powered applications, intelligent automation systems, and scalable backend services\. My work focuses on Large Language Models \(LLMs\), AI Agents, Agentic Workflows, Retrieval\-Augmented Generation \(RAG\), and production\-ready AI systems using Python, FastAPI, LangGraph, AWS, and PostgreSQL\. I began my career as a Frontend Developer, building responsive web applications with ReactJS and modern JavaScript frameworks\. Over time, I expanded into Data Analytics and AI Engineering, combining software engineering fundamentals with machine learning and generative AI technologies\. I enjoy designing and developing AI solutions that automate workflows, enhance decision\-making, and create measurable business impact\. My interests include Agentic AI, Multi\-Agent Systems, LLM Orchestration, AI Product Development, and scalable AI infrastructure\. I am currently seeking opportunities to build next\-generation AI products and intelligent systems that solve real\-world business problems\.

## Location

Bengaluru

## AI stack

antigravity

claude code

elevenlabs

grok

hermes agent

hugging face

## Work experience

Data Scientist at ScribeEMR Systems Private Limited, Aug 2026 \- Present · 1 mo, Designed and deployed enterprise\-grade AI and Generative AI solutions for healthcare documentation automation using Python, FastAPI, LangChain, LangGraph, OpenAI, Gemini, Claude, PostgreSQL, and AWS\. \* Built intelligent document understanding pipelines that transformed unstructured clinical guidelines into structured prompts and JSON schemas, reducing manual configuration effort by over 80%\. \* Developed and optimized multi\-LLM orchestration frameworks with dynamic model selection, fallback strategies, retry mechanisms, and concurrency controls to improve reliability, latency, and cost efficiency\. \* Evaluated and optimized LLM performance through prompt engineering, experimentation, and output validation, delivering production\-ready solutions for 100\+ healthcare providers with improved extraction accuracy and reduced hallucinations\. \* Designed multimodal AI pipelines using Vision Language Models to extract structured information from handwritten and scanned clinical documents, achieving 93–96% extraction accuracy while reducing inference costs by 52%\. \* Built AI\-powered speech intelligence pipelines using Whisper and Large Language Models to generate structured clinical documentation, extracting 25\+ medical entities with over 98% accuracy\. \* Analyzed model performance, monitored production metrics, and implemented continuous improvements to enhance accuracy, robustness, scalability, and operational efficiency\. \* Developed scalable backend services and data pipelines using FastAPI, PostgreSQL, asynchronous processing, RBAC, and GitLab CI/CD to support production AI systems\. \* Built agentic AI workflows using LangGraph, MCP, and N8N to automate reporting, notifications, and business processes, reducing backend processing latency by 95%\. \* Partnered with clinicians, product managers, and cross\-functional stakeholders to translate business requirements into AI\-driven solutions aligned with healthcare documentation standards\.

Gen AI Engineer at ScribeEMR Systems Private Limited, Aug 2025 \- Aug 2026 · 1 yr 1 mo, Designed and developed enterprise\-grade Generative AI applications for healthcare documentation automation using Python, FastAPI, LangChain, LangGraph, OpenAI, Gemini, Claude, PostgreSQL, and AWS\. • Built AI workflows that automatically transformed clinical guideline documents into structured prompts and JSON schemas, reducing manual configuration eﬀort by over 80%\. • Engineered reliable multi\-LLM orchestration pipelines with intelligent model routing, fallback strategies, retry mechanisms, and concurrency controls for production workloads\. • Developed production\-ready prompt engineering frameworks for 100\+ healthcare providers, improving extraction accuracy while minimizing hallucinations and ensuring consistent outputs\. • Designed multimodal AI pipelines to extract structured information from handwritten and scanned clinical documents using Vision Language Models, achieving 93–96% extraction accuracy while reducing inference costs by 52%\. • Built AI\-powered speech\-to\-documentation workflows using Whisper and LLMs to generate structured clinical notes, extracting 25\+ medical attributes with 98%\+ accuracy\. • Developed secure backend services with FastAPI, PostgreSQL, RBAC, asynchronous processing, and GitLab CI/ CD, enabling scalable deployment of AI services\. • Built agentic AI workflows using LangGraph, MCP, and N8N to automate internal reporting, notification systems, and business workflows, reducing backend latency by 95%\. • Collaborated with clinicians, product managers, operations teams, and business stakeholders to design AI solutions aligned with healthcare documentation standards\.

Data Analyst at Schoolknot, Aug 2024 \- Jun 2025 · 11 mos, Remote, • Developed and optimized data reporting solutions for a 1M\+ record ERP platform, improving reporting accuracy by 30% and enabling data\-driven decision\-making\. • Performed exploratory data analysis to uncover product adoption trends and user engagement gaps, providing insights that informed FY25 product strategy\. • Built executive Tableau dashboards for fee recovery, attendance, and operational KPIs, helping improve billing efficiency by 10%\. • Designed and launched an AI\-powered mock examination platform that delivered personalized performance analysis and automated student feedback using LLMs\. • Created intelligent assessment workflows to evaluate student responses, identify learning gaps, and generate targeted improvement recommendations\.

Software Developer at Encora Inc\., Jul 2022 \- Aug 2024 · 2 yrs 2 mos, Pune District, • Developed responsive web applications for healthcare and ed\-tech clients using ReactJS, JavaScript, HTML, and CSS, delivering intuitive and scalable user experiences\. • Built Python and SQL\-based analytics solutions that enabled large\-scale reporting, operational visibility, and data\-driven business decisions\. • Automated reporting and data\-processing workflows using Pandas, saving 40\+ hours of manual effort per month and improving reporting efficiency\. • Collaborated with cross\-functional teams on API integrations, database design, testing, and Agile delivery to ensure high\-quality software releases\. • Created reusable UI components and implemented unit testing best practices, improving application maintainability, consistency, and overall code quality\.

Junior Software Engineer at Encora Inc\., Jan 2022 \- Jun 2022 · 6 mos, Pune

Trainee software Engineer at Encora Inc\., Jun 2021 \- Dec 2021 · 7 mos, Pune, Maharashtra, India

## Education

Full Stack Data Science &amp; AI, AlmaBetter \(Accredited by IIT Guwahati\)

Bachelor of Engineering, Information Technology, Smt\.Kashibai Navale college of Engineering

## Public links

- github: https://github\.com/vanshikauttarwar1
- medium: https://medium\.com/@vanshikauttarwar14
- ds\-portfolio\-sepia\.vercel\.app: https://ds\-portfolio\-sepia\.vercel\.app/

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

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