You will get Enterprise AI Chatbot on Your Data (RAG) using LangChain & Neo4j
Project details
Standard AI chatbots often "hallucinate" or fail to connect the dots between different documents. I solve this by building GraphRAG systems combining the power of Vector Search with Knowledge Graphs (Neo4j).
I am a Python AI Engineer specializing in LangChain and LangGraph. I build autonomous agents that don't just "chat" they reason, plan, and execute tasks using your business data.
My Tech Stack (The "Pro" Suite):
Orchestration: LangChain & LangGraph (for cyclic, agentic workflows).
Database: Neo4j (Graph DB) & Vector Stores (Pinecone/Chroma).
LLMs: OpenAI (GPT-4o), Google Gemini 1.5 Pro, Llama 3.
Backend: Python (Django/FastAPI/Flask).
What You Get:
✅ Hybrid Search: Combines keyword search + vector semantic search for 99% accuracy.
✅ Memory: The bot remembers past conversations (Session History).
✅ Source Citations: The bot tells you exactly which document it used to answer.
✅ Complex Reasoning: Using LangGraph, the bot can break down complex user queries into steps.
Perfect For:
Legal & Medical Analysis (where accuracy is non-negotiable).
Internal Corporate Knowledge Bases.
Customer Support Agents that need to look up User IDs in a database.
I am a Python AI Engineer specializing in LangChain and LangGraph. I build autonomous agents that don't just "chat" they reason, plan, and execute tasks using your business data.
My Tech Stack (The "Pro" Suite):
Orchestration: LangChain & LangGraph (for cyclic, agentic workflows).
Database: Neo4j (Graph DB) & Vector Stores (Pinecone/Chroma).
LLMs: OpenAI (GPT-4o), Google Gemini 1.5 Pro, Llama 3.
Backend: Python (Django/FastAPI/Flask).
What You Get:
✅ Hybrid Search: Combines keyword search + vector semantic search for 99% accuracy.
✅ Memory: The bot remembers past conversations (Session History).
✅ Source Citations: The bot tells you exactly which document it used to answer.
✅ Complex Reasoning: Using LangGraph, the bot can break down complex user queries into steps.
Perfect For:
Legal & Medical Analysis (where accuracy is non-negotiable).
Internal Corporate Knowledge Bases.
Customer Support Agents that need to look up User IDs in a database.
Programming Languages
HTML & CSS, JavaScript, PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$300
|
Advanced
$999
|
|---|---|---|---|
| Delivery Time | 4 days | 10 days | 21 days |
Number of Revisions | 1 | 1 | 2 |
Design Customization | - | - | - |
Content Upload | - | - | - |
Responsive Design | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $250
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KW
Ken W.
Jun 30, 2026
AI bot trainner, paid per conversation
About Aftab
Python Developer | Chatbots | RAG | Generative AI/ML/LLMs
Usta Muhammad, Pakistan - 5:52 am local time
Core Expertise
Backend & APIs: Python (Django, Flask, FastAPI), RESTful APIs, authentication, and microservices
AI & Machine Learning: Model development, data preprocessing, and predictive analysis (Scikit-learn, TensorFlow, Pandas, NumPy)
Web Development: Full-stack web apps using Django + React , HTML, CSS, JavaScript
Web Scraping & Automation: Data extraction and task automation using BeautifulSoup, Selenium, and Python scripting
Databases: MySQL, SQLite, PostgreSQL - schema design, data handling, and optimization
Deployment & Integration: Git, Docker (basic), and API integration for connecting apps and external services
What I Deliver
✔️ Scalable and maintainable backend systems
✔️ AI/ML-based predictive or automation solutions
✔️ Web applications with responsive interfaces
✔️ Clean, documented, and tested code
✔️ Clear communication and on-time delivery
#PythonDeveloper #DjangoDeveloper #FlaskDeveloper #FastAPIDeveloper #AIMLEngineer #MachineLearning #DeepLearning #DataScience #WebScraping #Automation #APIIntegration #BackendDeveloper #FullStackDeveloper #DatabaseDeveloper #PostgreSQL #MySQL #SQLite #TensorFlow #ScikitLearn #BeautifulSoup #Selenium #WebDevelopment #RESTAPI #SoftwareEngineer #AIProjects #DataAnalysis #Chatbot
Steps for completing your project
After purchasing the project, send requirements so Aftab can start the project.
Delivery time starts when Aftab receives requirements from you.
Aftab works on your project following the steps below.
Revisions may occur after the delivery date.
Stop Hallucinations. Get a RAG Chatbot That Actually Understands Your Data