Retrieval-Augmented Generation system that indexes internal documentation and data sources — from concept to production. Full implementation: data ingestion, vector indexing, prompt engineering, and a web interface for end users.
Employees ask natural-language questions and get precise answers with source references. Built on vector databases with modern web interfaces. Optional integration into team collaboration tools.
RAG-based AI assistant for product and portfolio consulting — answers customer questions based on indexed product data, case studies, and service descriptions. The AI assistant can take on the role of a real person — e.g. the company founder who knows every product and advises customers in their own tone and style.