PG.
Available for Summer 2026 Internships

Hi, I'm Pranshu Ghori

AI Engineer · LLM Agents · RAG Systems

Building intelligent systems at the intersection of data, language, and autonomous AI.

4.0Cum. GPA
5+AI Agents Built
2027Graduation Year
LLM AgentsPrimary Focus

About Me

AI Engineer building production-grade agents and intelligent systems.

I'm pursuing concurrent degrees in B.S. Artificial Intelligence (STEM) and B.S. Business Data Analytics (STEM) at Arizona State University, maintaining a 4.0 GPA. My focus sits at the intersection of language models, autonomous agents, and real-world data systems.

I specialize in LLM engineering, agentic orchestration with LangGraph, and RAG pipeline design. From building multimodal compliance auditing systems on Azure — using Azure Video Indexer, Azure AI Search, and GPT-4o — to production RAG pipelines over FAISS and Pinecone, I engineer AI systems that reason, retrieve, and act with full observability via LangSmith and Azure Application Insights.

I'm particularly drawn to autonomous AI agents, domain-specific tooling, and applied generative AI — systems where language models move beyond chat and become reliable, observable components in production workflows. My ML engineering background in Scikit-learn and MLOps grounds the AI work in solid engineering fundamentals.

LLM Engineering

Prompt engineering, API integration, and chaining LLMs into reliable, production-grade pipelines.

Agentic Systems

Multi-agent orchestration with LangGraph — planning, tool use, reflection, and conditional routing.

RAG & Retrieval

Vector search, embeddings, and knowledge retrieval using FAISS, Pinecone, and Azure AI Search.

4.0
GPA @ ASU

Skills & Technologies

The stack I use to design, build, and deploy intelligent AI systems.

Agentic AI & LLM Engineering

LangChainLangGraphRAGPrompt EngineeringLLM EvaluationNLPOpenAI APIAnthropic ClaudeAzure OpenAIGPT-4oxAI GrokFAISSPineconeAzure AI SearchVector DatabasesEmbeddingsLangSmithAzure Application Insights

Machine Learning & Deep Learning

PyTorchTensorFlowScikit-learnTransformersLSTMsHugging FaceDeep LearningGenerative AIFine-TuningStatistical LearningFeature EngineeringComputer Vision

Software Engineering

PythonGoJavaSQLAlgorithms & Data StructuresScalable ArchitectureDesign PatternsFastAPIREST APIsGit/GitHub

Data & Visualization

PandasNumPyMatplotlibTableauPower BIExcelJupyterAlteryxAmazon RedshiftServiceNowAzure Video IndexerMLOps

Experience

My professional journey in data analytics and web technologies.

Data Analytics Assistant

Jun 2025 – Present
ET Network Infrastructure – Arizona State University
  • Analyzed network hardware inventory data in Python, Pandas, and SQL across 1,000+ assets — identifying discrepancies, null fields, and duplicate records to improve data quality for audit cycles.
  • Built automated ETL pipelines to clean, reconcile, and visualize inventory datasets using Python and Power BI — eliminating manual reconciliation steps and delivering recurring dashboards to infrastructure leadership.

Web Assistant

Dec 2024 – Jun 2025
Global HyPT Center – Arizona State University
  • Maintained 20+ university web pages using HTML and CSS; performed pre-publication QA validation catching layout breaks, dead links, and responsive failures before production.

ML Engineer Intern

May 2023 – Sep 2023
Bigscal Technologies Pvt. Ltd.
  • Assisted the ML engineering team building end-to-end production ML pipelines — contributing to data preprocessing, feature engineering, and model training workflows using Python and Scikit-learn.
  • Built and tested classification and regression models using Scikit-learn, supporting model selection, hyperparameter tuning, and performance benchmarking across multiple production use cases.
  • Supported MLOps workflows by contributing to model deployment and monitoring tasks — gaining hands-on experience with production-grade ML lifecycle management and pipeline integration.

Featured Projects

AI agents, RAG systems, and data pipelines — built end-to-end.

AI Focus

Video Compliance QA Pipeline

LangGraphAzure Video IndexerRAGAzure AI SearchAzure OpenAIGPT-4oLangSmithPython
  • Built a production-grade video compliance auditing system orchestrated by LangGraph — ingesting multimodal content via Azure Video Indexer (transcripts + OCR) and detecting regulatory violations using RAG powered by Azure AI Search and Azure OpenAI embeddings.
  • Engineered the core reasoning engine using GPT-4o to deterministically synthesize compliance rules against extracted video content, generating structured JSON reports.
  • Integrated LangSmith for LLM tracing and Azure Application Insights for production-grade telemetry and full-stack observability.
  • Designed end-to-end modular architecture with clean separation across ingestion, retrieval, reasoning, and reporting stages — deterministic outputs with deep observability at every layer.
AI Focus

Corporate Brochure Generator

PythonxAI GrokLLMWeb ScrapingJupyter
  • End-to-end pipeline that scrapes any corporate website and generates a polished company brochure
  • Fetches all links from a homepage, then uses Grok to filter only relevant pages (About, Products, Careers, etc.)
  • Scrapes each selected page and passes consolidated content to Grok for brochure generation
  • Outputs formatted Markdown ready for publishing or export
  • Modular structure: scraper.py handles all web utilities, brochure.ipynb orchestrates the full pipeline
AI Focus

DocumentLoader — Production RAG Pipeline

LangChainLangGraphFAISSOpenAIAnthropicFastAPIPython
  • Built a production-ready RAG pipeline supporting natural language Q&A over custom documents with streaming responses, source citations, and multi-turn memory — reducing retrieval latency via FAISS nearest-neighbor search and dynamic document ingestion at runtime.
  • Orchestrated the full retrieval-to-reasoning loop using LangChain and LangGraph — context retrieval, prompt construction, LLM chaining, and fallback handling.
  • Architected for full provider portability (FAISS → Pinecone, OpenAI → Anthropic) without re-architecting the pipeline.

California Housing Price Prediction

Pythonscikit-learnPandasNumPy
  • Built an end-to-end regression ML pipeline
  • Used stratified train/test split, preprocessing with ColumnTransformer, and unified Pipeline
  • Engineered predictive features like log transforms, ratio metrics, geo-cluster similarity
  • Evaluated using cross-validation and RMSE
  • Saved deployable artifact with joblib

U.S. Flight Delay & Cancellation Analysis

PythonPandasNumPyMatplotlibSeaborn
  • Analyzed 3 million U.S. flight records
  • Identified delay and cancellation patterns by airline, route, season, and operational cause
  • Engineered time-based features such as hour, weekday, and season
  • Found late aircraft and carrier operations were major contributors to delay minutes
  • Produced visual reports with actionable insights

Education

Arizona State University

Tempe, AZ

B.S. Business Data Analytics (STEM-Designated)

B.S. Artificial Intelligence (STEM-Designated)

Concurrent Degrees

Aug 2024 – Dec 2027

GPA:4.00/ 4.00
Dean's Honor List (Fall 2024, Spring 2025)

Get In Touch

Currently seeking Fall 2025 and Summer 2026 data analytics and ML internships.

Contact Information

Resume

Download my full resume to see a complete list of my skills, experiences, and academic achievements.

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