Upwork home
Sign up
Project Catalog
DesignDesign
Video & AudioVideo & Audio
Development & ITDevelopment & IT
MarketingMarketing
Writing & TranslationWriting & Translation
MoreMore

You will get Custom RAG AI Assistant (Chat with Your Data System)

Vira L.Status: Offline
Vira L. Vira L.
Preview image

Let a pro handle the details

Buy Other AI & Machine Learning services from Vira, priced and ready to go.
Vira L.Status: Offline
Vira L. Vira L.
Preview image

Let a pro handle the details

Buy Other AI & Machine Learning services from Vira, priced and ready to go.

Project details

I build production-ready RAG (Retrieval-Augmented Generation) systems that allow you to chat with your private data, documents, and knowledge base using AI.

This is not a simple chatbot - it is a structured AI search and reasoning system that retrieves relevant information from your data and generates accurate, source-backed answers.

The system can work with PDFs, documents, internal databases, manuals, policies etc.

Each solution is fully custom-built for production use, with focus on accuracy, scalability, and integration into your existing systems.

What is included:
• Data ingestion pipeline (PDFs, docs, databases)
• Embedding generation & vector database setup
• Semantic search implementation
• RAG pipeline (retrieval + generation logic)
• AI chat interface with your data
• Source citations & answer grounding
• API integration with your systems
• Backend development (Python / Node.js)
• Production deployment setup
• Full source code & documentation

Key technologies: RAG systems, OpenAI / Claude embeddings, vector databases (Pinecone / pgvector), Python, Node.js, PostgreSQL, LangChain (optional), Docker, API integration, cloud deployment
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System
AI Tools
Amazon SageMaker, Azure Machine Learning, MLflow, Open Neural Network Exchange, OpenCV, PyTorch, TensorFlow
AI Development Language
Python

What's included $2,000

These options are included with the project scope.

$2,000
  • Delivery Time 10 days
  • Number of Revisions 2
    • AI Model Integration
    • Detailed Code Comments
    • Knowledge Graph
    • Model Documentation
    • Source Code

Frequently asked questions

Vira L.Status: Offline

About Vira

Vira L.Status: Offline
LLM Agent Engineer | RAG & Multi-Agent Systems | Node.js, PHP/Laravel
Chernivtsi, Ukraine - 3:38 am local time
🤖 I build LLM-powered products: multi-agent systems, RAG pipelines, document AI - not chatbots, not experiments, but production systems for real businesses.

📦 What I deliver:
→ Multi-agent orchestration (LangChain, CrewAI, agent collaboration)
→ RAG pipelines with vector databases (pgvector, Pinecone, FAISS)
→ Document AI (extract data, fill forms, structured outputs)
→ Conversational assistants (tax, legal, internal tools)
→ LLM + ML combination (classification, analysis, predictions when needed)
→ Integration into existing apps (Node.js, Laravel, Python backend)
→ Full-stack implementation (backend, frontend, API, deployment)

💼 15+ years full-stack experience - Node.js, PHP/Laravel, Python, React, Vue.js, PostgreSQL, Docker, AWS. In the last few years, most of my work is AI built into real products: SaaS platforms, enterprise tools, internal automation.

📌 Recent projects:

1. Multi-agent document processor (Tech Lead)
→ Turns contracts into structured estimates through chat-based refinement
→ LangChain + GPT-4 + pgvector + multi-agent orchestration
→ Node.js backend, Vue.js frontend, Docker deployment

2. Conversational tax assistant
→ RAG system with vector DB for domain-specific knowledge
→ Extracts data from documents, fills forms, handles submission end-to-end
→ Python backend, React frontend, PostgreSQL

3. Market research AI service
→ LLM for automated report generation
→ ML (scikit-learn, pandas) for statistical analysis: crosstabs, conjoint, MaxDiff, sentiment
→ Laravel + Node.js + Vue.js, mobile apps with Flutter, payments, real-time sync

4. Video production AI pipeline
→ Multi-service platform for video processing automation
→ AI agents for transcription, summarization, metadata extraction
→ Python, FastAPI, AWS, Docker

🛠 Services I offer:
→ Build LLM agent from scratch (multi-agent, RAG, custom workflows)
→ Add AI to existing Laravel/Node.js/Python app
→ Document processing automation (extract → classify → output)
→ Conversational assistant for internal tools or customer support
→ LLM + ML combination for analytics/classification
→ API integration (OpenAI, Anthropic, Gemini, custom models)
→ Full-stack development (backend, frontend, deployment)

🔧 I can work on:
→ AI layer only (agents, RAG, prompts)
→ Backend only (Node.js, PHP, Python)
→ Frontend only (React, Vue, Angular)
→ Full stack (all of it)
→ Technical leadership (architecture, team coordination)

✉️ Tell me what you're building and where you're stuck - happy to take a look.

#LLMApplicationDevelopment, #AIAgentDevelopment, #RetrievalAugmentedGeneration, #RAG, #MultiAgentSystems, #LangChain, #OpenAIAPI, #ClaudeAPI, #GeminiAPI, #PromptEngineering, #ConversationalAI, #DocumentAI, #MachineLearning, #ArtificialIntelligence, #VectorDatabases, #pgvector, #Pinecone, #FAISS, #KnowledgeBaseAI, #SemanticSearch, #AIWorkflowAutomation, #DataExtraction, #OCR, #APIDevelopment, #APIIntegration, #RESTAPI, #NodeJS, #NestJS, #Python, #PHP, #Laravel, #PostgreSQL, #Redis, #Docker, #AWS, #TypeScript, #React, #VueJS, #FullStackDevelopment, #SaaSDevelopment

Steps for completing your project

After purchasing the project, send requirements so Vira can start the project.

Delivery time starts when Vira receives requirements from you.

Vira works on your project following the steps below.

Revisions may occur after the delivery date.

Requirements & Data Analysis

I analyze your documents, data sources, and use case to design the RAG system structure.

Data Ingestion Pipeline Setup

I build a pipeline to process PDFs, documents, databases, and other data sources.

Review the work, release payment, and leave feedback to Vira.