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You will get Turn Your Unstructured Data into a Queryable Knowledge Graph (GraphRAG)

Mohamed Khalil S.Status: Offline
Mohamed Khalil S. Mohamed Khalil S.
Preview imagePreview image

Let a pro handle the details

Buy Generative AI services from Mohamed Khalil, priced and ready to go.
Mohamed Khalil S.Status: Offline
Mohamed Khalil S. Mohamed Khalil S.
Preview imagePreview image

Let a pro handle the details

Buy Generative AI services from Mohamed Khalil, priced and ready to go.

Project details

Standard RAG systems often fail at understanding simple domestic relationships or complex "multi-hop" connections across your data. I will build a Knowledge Graph (KG) and a GraphRAG pipeline that allows your AI to navigate connections, not just keywords.

By transforming your unstructured data into a graph database (Neo4j), we enable:

Better Context: The AI understands how entities (People, Companies, Concepts) are actually related.
Multi-Hop Retrieval: Answers questions that require connecting multiple pieces of information across different documents.
Auditability: You can visually see the nodes and relationships the AI used to build its answer in Neo4j.
I use state-of-the-art tools including LangChain, LangSmith, and Neo4j/Cypher to ensure your GraphRAG is scalable and accurate.
AI Algorithms
Large Language Model, Multimodal Large Language Model
AI Applications
AI Chatbot, Natural Language Understanding
AI Development Language
Python
AI Tools
Azure OpenAI, Hugging Face, Streamlit, Word2vec
AI Models
BERT, ChatGPT
What's included
Service Tiers Starter
$40
Standard
$150
Advanced
$200
Delivery Time 2 days 7 days 7 days
Number of Revisions
123
AI Model Integration
Batch Normalization
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Database Integration
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Detailed Code Comments
Image Upscaling
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MLOps
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Model Deployment
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Model Documentation
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Model Monitoring
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Model Testing & Optimization
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Model Tuning
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Natural Language Processing
NLP Tokenization
Pre-Training
Prompt Engineering
Setup File
Source Code

Frequently asked questions

Mohamed Khalil S.Status: Offline

About Mohamed Khalil

Mohamed Khalil S.Status: Offline
AI Engineer | NLP Specialist
Monastir, Tunisia - 1:38 pm local time
I'm an AI Engineer with extensive hands-on experience building production-ready AI solutions, including advanced NLP, GenAI, conversational systems with real-time speech-to-text (STT) and text-to-speech (TTS), automation workflows, and RAG applications. I've delivered high-impact projects, including successful freelance work on Upwork. I'm passionate about creating efficient, scalable AI that drives real results for clients.

What I Offer:
✅ NLP & Generative AI: Fine-tuning transformers (e.g., T5, Mistral), custom tokenizers, semantic search, prompt engineering, and integration with LangChain, LangGraph, LangSmith, Atomic-Agents, Instructor, ReAct agents, etc.
✅ Conversational & Voice AI: Real-time speech-to-text (Whisper-timestamped), text-to-speech (Piper), speaker identification, offline assistants powered by Ollama LLMs, and streaming APIs with FastAPI/WebSockets.
✅ AI Agents & Automation: Custom workflows using n8n, AI agents powered by LLM providers like Google Gemini, GroqCloud, and OpenRouter, web scraping/RSS/Tavily Search integration, personalized content scoring, and multi-channel delivery (email, Telegram, WhatsApp).
✅ RAG & Knowledge Graphs: Retrieval-augmented generation systems (including GraphRAG), knowledge graph extraction and generation (Neo4j/Cypher), enhanced document comprehension, and research pipeline integrations.
✅ Machine Learning Systems: Recommendation engines using cosine similarity, data pipelines with preprocessing/optimization, model fine-tuning, quantization, and flash attention techniques.
✅ Full-Stack AI Integration: Building end-to-end applications with frontends (Angular, React, Gradio, Streamlit) and backends (Flask, FastAPI, Spring Boot), connecting AI models to intuitive UIs (including Unity-based interfaces).
✅ Deployment & DevOps: Docker containerization, cloud hosting on Azure/Railway, secure APIs with authentication, and persistent storage using Supabase, PostgreSQL, or NoSQL databases (ChromaDB, Neo4j).

Let's collaborate to bring your AI vision to life with innovative, high-performance solutions tailored to your needs! 🚀

Steps for completing your project

After purchasing the project, send requirements so Mohamed Khalil can start the project.

Delivery time starts when Mohamed Khalil receives requirements from you.

Mohamed Khalil works on your project following the steps below.

Revisions may occur after the delivery date.

Ontology Design

We define the Nodes and Relationships that represent your domain.

Extraction Pipeline

Implementation of LLM-based entity and relationship extraction from your raw data

Review the work, release payment, and leave feedback to Mohamed Khalil.