Generative AI
LLM applications, RAG systems, and grounded generation that turn model capability into useful interfaces.
Ritik Mishra / portfolio 2026
GenAI &
Agentic AI
Developer
I build intelligent applications using LLMs, RAG, AI agents, tool calling and modern AI engineering workflows.
Building at the intersection of models and software
Live system map / 01—05
01LLM
02RAG
03Agents
04Tools
05Applications
00 / What I build
AI engineering focus
Agentic AI
LangGraph, tool calling, MCP, and human-in-the-loop workflows for systems that can act with control.
AI engineering
APIs, workflows, deployment, and stateful applications built around practical delivery.
01 / Selected work
AI systems I’ve built
Four different ways to make intelligence useful: coding, retrieval, writing, and tools.
Agentic workflowAgentic AI
AI Coding Agent
An agentic coding assistant that plans tasks, inspects workspaces, calls tools, and coordinates local execution through a remote API.
System architecture remote / local
01User
02Streamlit UI
03FastAPI backend
04Task queue / backend state
05Local agent on user computer
06LangGraph
07MCP
08User workspace
- Streamlit
- FastAPI
- LangGraph
- MCP
- Render
- Multi-provider LLM fallback
Retrieval + generationGenerative AI
Enterprise RAG Knowledge Assistant
A document-grounded knowledge assistant that ingests common business files, retrieves relevant context, and generates grounded answers.
Retrieval workflow verified flow
Documents↓
Chunking↓
Embeddings↓
FAISS↓
Top-4 retrieval↓
Context↓
Gemini↓
Answer
- Streamlit
- LangGraph
- FAISS
- BAAI/bge-small-en-v1.5
- Gemini 2.5 Flash
Content workflowGenerative AI
AI Blog Writing Agent
A LangGraph-based multi-step content generation system that routes topics, researches when needed, and produces structured Markdown.
Generation workflow verified flow
Topic↓
Router↓
Research↓
Evidence↓
Planner↓
Workers↓
Reducer↓
Markdown
- Python
- Streamlit
- LangGraph
- Google Gemini 2.5 Flash
- LangChain
- Tavily
- Pydantic
- Pandas
- Markdown
Tool-using assistantGenerative AI
Multi-Utility AI Chatbot
A multi-tool GenAI assistant combining PDF RAG, web search, stock lookup, calculator tools, and LangGraph workflows.
Tool calling surface 4 utilities
LLMagent
RAG
Search
Stock
Calculator
- Python
- Streamlit
- LangChain
- LangGraph
- Gemini 2.5 Flash
- FAISS
- HuggingFace Sentence Transformers
- SQLite
- PyPDF
- DuckDuckGo Search
- Alpha Vantage API
02 / Supporting foundation
Machine learning projects
A compact foundation across NLP, classification, recommendations, and regression.
NLP / binary text classificationMachine Learning
SMS Spam Detection
A binary text-classification project for distinguishing SMS spam from legitimate messages.
- Python
- Pandas
- NumPy
- Scikit-learn
- NLTK
- Matplotlib
- Seaborn
- WordCloud
- XGBoost
Binary classificationMachine Learning
Customer Churn Prediction
A binary-classification application that predicts customer churn from customer, service, contract, and billing features.
- Python
- Pandas
- NumPy
- Scikit-learn
- Streamlit
- Pickle
Content-based recommendationsMachine Learning
Movie Recommendation System
A content-based recommendation system that finds similar movies from metadata and fetches posters through TMDB.
- Python
- Pandas
- NumPy
- Scikit-learn
- NLTK
- Streamlit
- Requests
- TMDB API
Machine Learning — RegressionMachine Learning
Car Price Prediction
A machine learning model that predicts used-car selling prices from vehicle and ownership-related features.
- Python
- Pandas
- NumPy
- Scikit-learn
- XGBoost
- Matplotlib
- Seaborn
03 / AI stack
AI stack & capabilities
The tools and systems I use to build LLM applications, agentic workflows, and practical AI products.
01
GENERATIVE AI
- LLM Applications
- RAG
- Transformers
- Embeddings
- Vector Search
- Semantic Search
- LangChain
- Prompt Engineering
- Hugging Face
02
AGENTIC AI
- AI Agents
- LangGraph
- Tool Calling
- MCP
- MCP Python SDK
- Agent Orchestration
- Human-in-the-loop
- Stateful Workflows
03
AI ENGINEERING
- FastAPI
- Streamlit
- Pydantic
- REST APIs
- SQLite
- API Integration
- Deployment
- AI Workflows
04
ML / DL FOUNDATION
- Scikit-learn
- TensorFlow
- Keras
- NLP
- Regression
- Classification
- Feature Engineering
- Model Evaluation
- Ensemble Learning
- CNN
- Transfer Learning
CORE/Python·SQL·Git·GitHub
04 / Background
Experience & education
The verified foundation behind the work.
17 November 2025 – February 2026 · 3 months
Data Science Intern — Tech Team
Adviktech Beat Services (OPC) Private Limited
Greater Noida West, Sector 4, Uttar Pradesh·Reporting Manager: Pawan Panchal
- Data collection, cleaning, and preprocessing
- Exploratory data analysis
- Statistical methods and machine learning algorithms
- Predictive model development and evaluation
- Pandas, NumPy, Scikit-learn, and Matplotlib
- Data visualization, dashboards, reports, and documentation
Education
Graduation year: 2026
B.Tech in Information Technology
Gautam Buddha University
CGPA: 8.35/10
Resume