Visualize OpenSearch hybrid search with BM25, vectors, analyzers, and ingest pipelines
No sign-up required • Free to try
Build semantic search with embeddings, hybrid retrieval, rerankers, and feedback analytics
Diagram ingestion, embeddings, metadata filters, and hybrid dense + sparse search
Diagram Weaviate classes, modules, hybrid search, and tenancy for semantic apps
Common questions about ai opensearch vector architecture generator
Use BM25 for lexical scoring and kNN plugin for vectors. Combine scores or rerank for relevance.
Use OpenSearch ingest nodes for text cleanup, field extraction, and embedding generation before indexing.
Enable TLS, fine-grained access controls, tenants, and audit logging. Limit access by role.
Shard by volume and usage, use replicas for HA, and monitor hot shards. Tune thread pools for kNN workloads.
Pick analyzers per language, use stopwords and synonyms. Align analyzers with query needs.
Signing up costs nothing and every feature is included. Only AI generation is metered, in credits.