You will get a custom RAG AI assistant with your content for business or creators
Project details
What You'll Get
A fully customized Retrieval-Augmented Generation (RAG) system using your specific documents to create an AI assistant that delivers accurate, context-aware responses. Complete with source code, detailed comments, local vector database integration, and 2 revision rounds.
How It Works
Your documents are processed, chunked, and embedded into a vector database for efficient semantic search. When you ask questions, the system retrieves the most relevant information and feeds it to an LLM to generate accurate, contextual responses based on your proprietary data.
My Expertise
As a Senior ML Engineer with 7+ years of experience, I've:
• Built 25+ AI systems processing 10K+ weekly requests
• Developed context-aware RAG with Qdrant achieving 90% query
• Reduced infrastructure costs by 40% through
• Created LLM systems with 25% performance improvement via data
• Implemented vector databases with hybrid retrieval techniques
I'll leverage my RAG system expertise to deliver a solution tailored to your specific needs, ensuring high accuracy and performance.
A fully customized Retrieval-Augmented Generation (RAG) system using your specific documents to create an AI assistant that delivers accurate, context-aware responses. Complete with source code, detailed comments, local vector database integration, and 2 revision rounds.
How It Works
Your documents are processed, chunked, and embedded into a vector database for efficient semantic search. When you ask questions, the system retrieves the most relevant information and feeds it to an LLM to generate accurate, contextual responses based on your proprietary data.
My Expertise
As a Senior ML Engineer with 7+ years of experience, I've:
• Built 25+ AI systems processing 10K+ weekly requests
• Developed context-aware RAG with Qdrant achieving 90% query
• Reduced infrastructure costs by 40% through
• Created LLM systems with 25% performance improvement via data
• Implemented vector databases with hybrid retrieval techniques
I'll leverage my RAG system expertise to deliver a solution tailored to your specific needs, ensuring high accuracy and performance.
AI Algorithms
Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, StyleGAN, Transformer Model, Variational Autoencoder, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Speech, AI-Generated Code, Automatic Speech Recognition, Conversational AI, Image Analysis, Natural Language Generation, Natural Language Understanding, Object Detection, Sentiment Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, GitHub Copilot, Hugging Face, Jasper AI, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
AlphaCode, BERT, ChatGPT, DALL-E, GPT-3, GPT-4, LaMDA, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included $90
These options are included with the project scope.
$90
- Delivery Time 3 days
- Number of Revisions 2
- AI Model Integration
- Database Integration
- Detailed Code Comments
- Source Code
About Andrey
Senior ML Engineer | LLM & RAG Systems Architect
100%
Job Success
Denpasar, Indonesia - 5:02 am local time
🏆 Key Achievements
- Architected 25+ AI systems processing 10K+ weekly requests, generating $1M+ revenue and 40% cost reduction
- Built context-aware RAG with Qdrant achieving 90% query relevance while reducing infrastructure costs by 40%
- Implemented MLOps pipelines with AWS/GCP and Docker/K8s, reducing deployment cycles by 60%
- Enhanced domain-specific LLM performance by 25% through data augmentation and custom evaluation
- Developed AI code detection system with 85% accuracy using AST parsing and LoRA fine-tuning
- Created data-driven decision frameworks aligning technical metrics with business KPIs
🎯 Client Benefits
- End-to-end AI solutions from concept to production with measurable ROI
- Enterprise-ready systems with scalable architecture and robust API integrations
- Custom RAG implementations optimized for your specific business domain
- Data scraping and ETL pipeline development for building high-quality AI training datasets
- Business intelligence dashboards for monitoring AI system performance
- Continuous optimization of ML workflows to reduce operational costs
🛠️ Technical Expertise
- AI/ML: LLM integration, RAG systems, Prompt Engineering, Vector Embeddings, LangChain, Hugging Face
- Development: Python, SQL, REST API, API Integration, FastAPI
- Data: Data Analysis, ETL Pipelines, Data Scraping/Mining, Data Visualization, Dashboard Development
- Infrastructure: AWS, GCP, Docker, Kubernetes, CI/CD, DevOps, Workflow Automation
- AI Applications: Chatbots, Recommendation Systems, Document Processing, Semantic Search
💼 Collaborative Approach
I translate complex requirements into effective business solutions with clear ROI. My workflow emphasizes stakeholder communication, technical excellence, and business-aligned metrics to ensure your AI projects deliver tangible value.
Steps for completing your project
After purchasing the project, send requirements so Andrey can start the project.
Delivery time starts when Andrey receives requirements from you.
Andrey works on your project following the steps below.
Revisions may occur after the delivery date.
Documents are processed, embedded into a vector database
System uses semantic search to find relevant information