Find what your users are looking for · even if they can't express it exactly
Exact keyword search is dead. Your users type intentions, not keywords. A catalogue of 10,000 products with exact search returns zero results for "comfort long-walk shoe" if the product is called "premium orthopedic insole". The semantic search engine understands the intent behind the query and returns the most relevant results, even with different terms.
Keyword-based search engines have a zero-result rate of 20–40% on e-commerce catalogues. Users abandon after two failed attempts. Poor internal search costs lost sales and a bad user experience.
Your content (products, articles, documents) is encoded as semantic vectors and stored in Pinecone, Weaviate or Elasticsearch. With each search, the query is encoded the same way and the semantically closest results are returned · regardless of the exact words used. Hybrid re-ranking (semantic + popularity + business filters) refines relevance.
Import and vector encoding of your catalogue, knowledge base or document corpus. PDF, HTML, JSON, CSV supported.
Embedding model selection (OpenAI, Cohere, sentence-transformers), vector database setup and business filters.
REST API or JavaScript SDK to integrate the engine into your site, mobile app or internal tool. Response time < 200ms.
Analysis of zero-result queries, embedding adjustment, A/B testing of re-ranking strategies.
Semantic search understands intent and always returns relevant results, even for imprecise queries.
Users who find what they're looking for buy. Relevant search is one of the best e-commerce conversion levers.
Every new product or document is indexed in seconds. The engine always reflects your current catalogue state.
Free 30-minute audit. We analyze your context and deliver a concrete roadmap.