You will get a custom RAG AI Chatbot for your documents
Project details
Most AI services provide a simple prompt; I provide a complete Engineering Ecosystem. What sets this project apart is the bridge between technical precision and production-ready execution.
I don’t just build chatbots; I architect secure, high-speed backends using FastAPI and Docker that are ready to scale the moment they are delivered. My approach prioritizes data privacy and architectural integrity, ensuring your AI is a reliable business asset that cites its sources, handles complex reasoning, and avoids the common pitfalls of standard LLM implementations.
I don’t just build chatbots; I architect secure, high-speed backends using FastAPI and Docker that are ready to scale the moment they are delivered. My approach prioritizes data privacy and architectural integrity, ensuring your AI is a reliable business asset that cites its sources, handles complex reasoning, and avoids the common pitfalls of standard LLM implementations.
AI Algorithms
Autoencoder, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Linear Discriminant Analysis, Long Short-Term Memory Network, Multilayer Perceptron, Recurrent Neural Network, Regression Analysis, Transformer ModelAI Applications
AI Chatbot, AI Text-to-Image, Facial Recognition, Image Recognition, Machine Translation, Natural Language Generation, Neural Machine Translation, Neural Style Transfer, Object Detection, Speech Synthesis, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
GitHub Copilot, PyTorch, Streamlit, TensorFlowAI Models
ChatGPT, GPT-3, GPT-4, LLaMA, Naive Bayes Classifier, OpenAI CodexWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$850
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 1 | 2 |
AI Model Integration | |||
Batch Normalization | - | ||
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | - | - | |
MLOps | - | - | |
Model Deployment | - | - | |
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | |||
Model Tuning | - | - | |
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
About Abdullah
AI Engineer
Kasur, Pakistan - 11:44 am local time
Steps for completing your project
After purchasing the project, send requirements so Abdullah can start the project.
Delivery time starts when Abdullah receives requirements from you.
Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery and Data Assessment
We begin by analyzing your specific use case and data format (PDFs, SQL, Web, etc.). I evaluate your requirements to determine the best LLM (e.g., GPT-4o, Claude 3.5, or Llama 3) and Vector Database for your unique project goals.
Architecture and Data Ingestion
I design the system architecture and set up the ingestion pipeline. This involves document chunking, choosing the right embedding model, and indexing your data into a high-performance vector store like ChromaDB, Pinecone, or FAISS.