AI-based Product Search Engine
We help companies transform how they search product data by combining vector databases with AI-driven semantic search. We design tailored solutions that understand meaning and context—not just keywords. Using Retrieval-Augmented Generation (RAG), our approach ensures accurate, relevant results while keeping the AI strictly guided by your trusted company data.
Vector Database & AI Search Solutions
We specialize in helping companies unlock smarter product search by combining vector databases with AI-powered semantic search. Instead of relying only on keywords, we design solutions that understand the meaning and context of every query, giving your teams faster and more accurate results.
With our expertise in vector databases (FAISS, OpenSearch, Pinecone) and Retrieval-Augmented Generation (RAG), we integrate AI directly with your trusted company data. This ensures the AI works only with your internal database content—empowering your processes while keeping control over how the AI reasons and responds.
Our tailored solutions make it possible to:
Find the right products even with typos, abbreviations, or vague descriptions.
Suggest similar or alternative products that may be relevant.
Speed up daily work with large product catalogs, even without knowing exact names or codes.
By embedding and indexing your database, AI can understand the content and deliver precise, contextual answers—going beyond simple word matches.
How our tailored solutions work – step by step
Query from frontend
The user enters a query in the web interface.
Receiver Layer
Securely accepts the query and connects to your company database.
Vector Retrieval
Fetches the most relevant products using semantic similarity (meaning-based search, not only words).
Ranking & Explanation Layer
Ranks candidates against the query and adds explanations:
Exact match? Yes/No
If No: shows what differs (e.g., size, material, compatibility)
Response to frontend
Delivers results as a clear list view (product name, link, similarity score, “Exact match?” flag, and explanation).