AI Solutions
RAG (Retrieval-Augmented Generation)
Vector databases and precise search of corporate knowledge to eliminate AI hallucinations and instant access to proprietary company information.
- 99.8%
- Relevant Context Sampling Accuracy
- < 150ms
- Semantic Vector Search Time
- 0%
- Risk of leakage of proprietary corporate documents
Are you facing these issues?
Hallucinations and made-up facts in AI responses
Standard models do not know the specifics of your business, regulations and prices, producing inaccurate or outdated information.
Solution
We implement hybrid semantic search (Dense + Sparse), rerankers and contextual submission of exact excerpts from company documents.
Difficulty handling heavy unstructured databases
The enterprise knowledge base is scattered across PDFs, spreadsheets, chats, and Notion, making it difficult to quickly extract relevant context.
Solution
We deploy automatic ETL pipelines for preprocessing, smart splitting and regular vectorization of updates.