You will get LLM Powered Systems Development with RAG & Fine-tuning Expertise
Project details
I will build a fully customized, production-ready LLM-powered system designed around advanced Retrieval-Augmented Generation (RAG) and fine-tuning to maximize accuracy, reliability, and intelligence across your documents or data sources.
Using state-of-the-art open-source or API-based models (LLaMA, Qwen, Mistral, GPT, etc.), I will create an AI system capable of understanding your content, retrieving the right information, and generating high-quality responses. The solution includes complete document ingestion, embedding generation, vector database setup, pipeline orchestration, and optional model fine-tuning for domain-specific expertise.
Your final deliverable is a robust, scalable LLM system deployed with a clean API interface, ready for integration into your product, automation workflow, or internal tools.
This project is ideal for companies seeking smarter search, automated support, knowledge base intelligence, or domain-trained AI assistants.
Using state-of-the-art open-source or API-based models (LLaMA, Qwen, Mistral, GPT, etc.), I will create an AI system capable of understanding your content, retrieving the right information, and generating high-quality responses. The solution includes complete document ingestion, embedding generation, vector database setup, pipeline orchestration, and optional model fine-tuning for domain-specific expertise.
Your final deliverable is a robust, scalable LLM system deployed with a clean API interface, ready for integration into your product, automation workflow, or internal tools.
This project is ideal for companies seeking smarter search, automated support, knowledge base intelligence, or domain-trained AI assistants.
AI Algorithms
Convolutional Neural Network, Feedforward Neural Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Hugging Face, PyTorch, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMAWhat's included $800
These options are included with the project scope.
$800
- Delivery Time 15 days
- Number of Revisions 5
- AI Model Integration
- Database Integration
- Detailed Code Comments
- Model Deployment
- Model Documentation
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- NLP Tokenization
- Prompt Engineering
- Setup File
- Source Code
Optional add-ons
You can add these on the next page.
Additional Revision
+$50
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YA
Yasser A.
Nov 24, 2025
AI Developer Needed – Google Reviews Analysis Platform (Sentiment, Classification & Summary)
About Ahmed
Data science and Machine learning Engineer
Rabat, Morocco - 3:40 am local time
Core Expertise:
▸ Generative AI & LLMs: Fine-tuning models (GPT, LLaMA, Qwen, DeepSeek), prompt engineering, RAG systems, LangChain
▸ Conversational AI: Chatbots using DialogFlow, Watson, RASA, AWS Lex; voice systems with VAPI, Retell, Twilio
▸ Multimodal AI: Vision-Language Models (VLMs), Vision-Language-Action Models (VLAs), multimodal perception and reasoning
▸ Machine Learning: Predictive modeling, classification, forecasting, recommendation systems, customer churn analysis
▸ Deep Learning: Neural networks (CNN, RNN, R-CNN, YOLO, SSD), emotion detection, transfer learning
▸ NLP: Sentiment analysis, NER, summarization, BERT, GPT-3, text classification
▸ Computer Vision: Object detection, facial recognition, image classification, OpenCV
▸ CRM Integration & Automation: HubSpot, Salesforce, Zoho; workflow automation, lead qualification, sentiment analysis, email personalization, meeting scheduling
▸ Automation: Web scraping (BeautifulSoup, Selenium, Scrapy), workflow automation, API integration
My academic journey and professional experience have given me a solid foundation in AI, deep learning, and programming, along with practical skills in building and deploying sophisticated machine learning models. I enjoy bridging the gap between cutting-edge research and practical application, turning innovative ideas into effective solutions that create a tangible impact.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Training the Model and implementing the advanced RAG.
Training the Model and constructing the vector database for the advanced RAG pipeline with query → retrieval → answer, implementing a document ingestion pipeline.
Deployment & API
Deploying the Model and constructing an API endpoint