Vector Search
Production-grade semantic search infrastructure — for RAG systems, recommendation engines, and any application that needs to find by meaning, not just keywords.
Search by Meaning, At Enterprise Scale
Modern AI applications — RAG, copilots, recommendation engines, anomaly detection — all rest on the same foundation: fast, accurate vector search across enterprise content. Apptad Vector Search delivers that foundation as production infrastructure, with the embeddings, indexing, hybrid retrieval, and access control that turn experiments into shippable products.
The Semantic Layer Behind Your AI Apps
Vector Search ingests your structured and unstructured content, generates embeddings with the right models, indexes for sub-50ms retrieval, and serves a hybrid (vector + keyword + filter) API that returns the right context — every time. Built for the realities of enterprise data: permissions, freshness, multitenancy, and audit.
Multi-Model Embeddings
OpenAI, Cohere, Voyage, open-source — choose the right embedding model per use case, swap freely.
Hybrid Retrieval
Combine vector similarity, BM25, and metadata filters in a single query for precision plus recall.
Permission-Aware
Row-level access control honored at retrieval time — users see only what they're allowed to see.
Continuous Sync
Connectors for SharePoint, Confluence, Drive, S3, and databases keep your index fresh automatically.
Everything You Need to Ship Semantic Search
A platform — not a library. Ingestion, indexing, retrieval, governance, and observability in one stack.
Document Ingestion
PDF, DOCX, HTML, code, transcripts — chunked intelligently with structure-aware parsing.
Vector + Keyword Hybrid
Single API combines dense vectors, sparse BM25, and metadata filters with tunable weights.
RAG-Ready Endpoints
Drop-in retrieval API for LangChain, LlamaIndex, custom agents, and direct LLM grounding.
Recommendations & Similarity
Find similar products, similar customers, similar tickets — semantic similarity at sub-50ms.
Quality & Drift Monitoring
Track retrieval quality over time — recall, precision, and embedding drift, with auto-reindex.
Enterprise Governance
Multi-tenant, SOC 2 Type II, fine-grained ACL, audit logs, and BYOK encryption.