A specialized database optimized for storing and querying high-dimensional vectors (embeddings) for similarity search.
Vector databases like Pinecone, Weaviate, Chroma, and pgvector enable fast nearest-neighbor search over millions of embeddings. They're the backbone of RAG systems, recommendation engines, and semantic search applications.
Storing embeddings of your knowledge base articles in Pinecone so an AI chatbot can find the most relevant documentation for each customer question.
Vector databases make AI applications practical by enabling sub-second retrieval of relevant context from large datasets, critical for production RAG systems.
The field focused on ensuring AI systems behave as intended, don't cause harm, and remain aligned wi...
A neural network component that allows models to focus on the most relevant parts of the input when ...
AI systems that can interpret and understand visual information from images and video.
A centralized repository optimized for analytical queries, storing structured historical data from m...
Numerical representations of text that capture semantic meaning for AI processing.
Need help implementing this in your business?
Get Started