You will get Custom AI Chatbot with LLM, RAG & API Integration
Project details
You will get a custom AI chatbot built around your business requirements, data, and workflow — not a generic chatbot template.
I can build intelligent assistants using LLMs, RAG, vector search, knowledge bases, APIs, and Python-based AI pipelines to help users find information, ask questions, automate repetitive tasks, and interact with business data.
Depending on your requirements, the solution can include:
• Custom AI chatbot development
• LLM integration
• RAG & semantic search
• Document/knowledge-base Q&A
• PDF and website knowledge sources
• Vector database integration
• OpenAI/Gemini and other LLM APIs
• Custom API integrations
• Conversation memory
• Prompt engineering
• Python/FastAPI backend
• Authentication and API security
• Testing and response optimization
• Deployment assistance
The goal is to deliver an AI assistant that produces useful, relevant, and context-aware responses based on your actual data and business requirements.
You will receive clean implementation, source code, documentation, and a solution designed so it can be extended as your requirements grow.
I can build intelligent assistants using LLMs, RAG, vector search, knowledge bases, APIs, and Python-based AI pipelines to help users find information, ask questions, automate repetitive tasks, and interact with business data.
Depending on your requirements, the solution can include:
• Custom AI chatbot development
• LLM integration
• RAG & semantic search
• Document/knowledge-base Q&A
• PDF and website knowledge sources
• Vector database integration
• OpenAI/Gemini and other LLM APIs
• Custom API integrations
• Conversation memory
• Prompt engineering
• Python/FastAPI backend
• Authentication and API security
• Testing and response optimization
• Deployment assistance
The goal is to deliver an AI assistant that produces useful, relevant, and context-aware responses based on your actual data and business requirements.
You will receive clean implementation, source code, documentation, and a solution designed so it can be extended as your requirements grow.
Machine Learning Tools
BERT, ChatGPT, Keras, NumPy, OpenCV, pandas, Python, PyTorch, SQL, TensorFlow, Vertex AIWhat's included
| Service Tiers |
Starter
$50
|
Standard
$120
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 5 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 1 | 2 | 2 |
Number of Scenarios | 3 | 5 | 8 |
Number of Graphs/Charts | 0 | 1 | 1 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
About M Asad
Machine Learning Engineer | AI, LLM, RAG & Computer Vision
Lahore, Pakistan - 1:38 am local time
I’m a Machine Learning Engineer and Python Developer specializing in building practical AI and machine learning solutions from model development to API and application integration.
My core expertise includes:
• Machine Learning & Deep Learning
• Python, TensorFlow, Keras & Scikit-Learn
• LLM Applications, RAG & AI Agents
• LangChain & LangGraph
• Vector Databases — FAISS, Chroma & Qdrant
• NLP & AI Chatbots
• Computer Vision, OpenCV & YOLO
• FastAPI & REST APIs
• Predictive Analytics & Data Analysis
• React, Streamlit, Docker & Git/GitHub
I have professional experience designing and deploying ML services across NLP, computer vision, and predictive analytics. I’ve also built FastAPI-based REST APIs for ML models and integrated AI features into web applications.
My project experience includes an LLM-powered RAG assistant with agentic workflows, an agriculture AI assistant with English/Urdu chatbot support, a multimodal emotion-based recommendation system, a real-time fire detection system, and a YOLO-based object detection application.
I focus on building solutions that are practical, reliable, and ready to move beyond a basic prototype.
If you need help with an AI/ML model, RAG application, AI agent, computer vision system, predictive analytics solution, or FastAPI ML backend, I’d be happy to help.
Let’s turn your AI idea into a working solution.
Steps for completing your project
After purchasing the project, send requirements so M Asad can start the project.
Delivery time starts when M Asad receives requirements from you.
M Asad works on your project following the steps below.
Revisions may occur after the delivery date.
Analyze Requirements & AI Workflow
Review the business requirements, data sources, chatbot goals, integrations, and expected user experience.
Build LLM & RAG Pipeline
Configure the AI model, document processing, embeddings, retrieval pipeline, prompts, and conversational logic.