0%0%Your company's knowledge is scattered across drives, wikis, email, and ERPs — and keyword search can't find what's phrased differently than it was filed. Dezvo builds AI search and knowledge management systems that understand meaning: semantic search over every source, permission-aware results, and answers with citations instead of ten blue links.
AI-powered enterprise search converts your documents into embeddings — numerical representations of meaning — so a query like “refund rules for damaged goods” finds the policy titled “Return & Compensation Guidelines” even though they share no keywords. Combined with an LLM, it returns a direct answer with citations to the source documents.
Production systems layer three techniques: vector search for meaning, keyword (BM25) search for exact terms like SKUs and codes, and reranking to order the merged results. Add permission filtering — people only see what they're allowed to — and you have knowledge management people actually use.
Embedding-based retrieval over documents, tickets, and wikis — tuned chunking, domain-adapted embeddings, and reranking for precision.
Vector search for meaning plus BM25 for exact matches — part numbers, invoice IDs, legal clauses — merged and reranked. Neither alone is enough.
Entities and relationships extracted from your content — people, products, projects — powering Graph RAG for questions plain retrieval can't answer.
OCR, layout parsing, and table extraction so PDFs, scans, and spreadsheets become searchable knowledge instead of dead files.