Vector representations of meaning
Text and images encoded as vectors for similarity search: the substrate of RAG and vector databases.
Vector representations of content enabling semantic search, clustering and RAG: the substrate of modern retrieval.
Who it's for
Teams building semantic search, recommendations or RAG over unstructured data.
Keep exploring
16 in catalog
Embeddings is featured by
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Cohere
The enterprise RAG platform
AI as a Service -
Pinecone
The vector database for AI
Vector Database -
Qdrant
The vector search engine
Vector Database -
Weaviate
The vector database with hybrid search
Vector Database -
Chroma
The AI-native embedding database
Vector Database -
Milvus
The vector DB built for scale
Vector Database -
pgvector
Vector search inside Postgres
Vector Database -
Turbopuffer
Serverless vector search on object storage
Vector Database -
LanceDB
The embedded vector database
Vector Database -
OpenAI
Advancing artificial intelligence to create transformative applications for individuals and businesses.
AI as a Service -
Google Gemini
Build with Google's best AI models
AI as a Service -
sqlite-vec
A vector search SQLite extension that runs anywhere
Vector Database -
Voyage AI
Supercharging search and retrieval for unstructured data
AI as a Service -
Jina AI
Your search foundation, supercharged
Service -
Vespa
AI search at scale
Vector Database -
DeepInfra
AI inference, fast, simple, reliable, low-cost
AI as a Service