AI Knowledge Systems & RAG Serhii Vysochanskyi
Turn your data into an AI system that gives accurate, context-aware answers.
I build Retrieval-Augmented Generation (RAG) systems that connect your data with AI - so your team and customers can get instant, reliable insights.
No more searching through documents, tools, or databases
What you get:
AI assistant trained on your data
Integration with documents, databases, and APIs
Vector database setup & retrieval pipelines
чат або API interface
Scalable, production-ready architecture
What I can connect:
PDFs, documents, Notion, Google Drive
Internal databases & CRM systems
APIs and structured data sources
Use cases:
Internal knowledge assistant for teams
Customer support AI trained on your docs
Sales enablement tools
Data search & insights systems
Tech stack:
OpenAI, Python, vector databases, embeddings, APIs, cloud infrastructure
Outcome:
An AI system that understands your data and delivers fast, accurate answers - reducing manual work and improving decision-making.
Not sure if RAG is the right approach?
Start with a Discovery Sprint - we’ll validate your use case and architecture.
FAQs
RAG (Retrieval-Augmented Generation) is a way to connect AI with your own data, so it gives accurate and context-aware answers instead of generic responses.
Most RAG systems take 2–4 weeks depending on data complexity and integrations.
We can work with documents, databases, APIs, and internal tools.
Yes - RAG systems are designed to retrieve relevant data before generating answers, which significantly improves accuracy.
Serhii's other services
Starting at$2,999
Duration3 weeks
Tags
OpenAI
Python
AI Automation
AI Chatbot Developer
Data Engineer
ML Engineer
Artificial Intelligence
AI automations
Service provided by
Serhii Vysochanskyi proLviv, 79000
- 3
- Followers
AI Knowledge Systems & RAG Serhii Vysochanskyi
Starting at$2,999
Duration3 weeks
Tags
OpenAI
Python
AI Automation
AI Chatbot Developer
Data Engineer
ML Engineer
Artificial Intelligence
AI automations
Turn your data into an AI system that gives accurate, context-aware answers.
I build Retrieval-Augmented Generation (RAG) systems that connect your data with AI - so your team and customers can get instant, reliable insights.
No more searching through documents, tools, or databases
What you get:
AI assistant trained on your data
Integration with documents, databases, and APIs
Vector database setup & retrieval pipelines
чат або API interface
Scalable, production-ready architecture
What I can connect:
PDFs, documents, Notion, Google Drive
Internal databases & CRM systems
APIs and structured data sources
Use cases:
Internal knowledge assistant for teams
Customer support AI trained on your docs
Sales enablement tools
Data search & insights systems
Tech stack:
OpenAI, Python, vector databases, embeddings, APIs, cloud infrastructure
Outcome:
An AI system that understands your data and delivers fast, accurate answers - reducing manual work and improving decision-making.
Not sure if RAG is the right approach?
Start with a Discovery Sprint - we’ll validate your use case and architecture.
FAQs
RAG (Retrieval-Augmented Generation) is a way to connect AI with your own data, so it gives accurate and context-aware answers instead of generic responses.
Most RAG systems take 2–4 weeks depending on data complexity and integrations.
We can work with documents, databases, APIs, and internal tools.
Yes - RAG systems are designed to retrieve relevant data before generating answers, which significantly improves accuracy.
Serhii's other services
$2,999