Vector Tree
Accurate, contextual vector retrieval for AI applications, at a massive scale.
We are revolutionizing the scalability of Vector Databases for AI applications, using a patented database structure that already handles a hundred billion vectors in visual search applications.
Our Vector Databases also support contextual relations by clustering vectors based on sources or other criteria.
Vector Databases for AI
Many AI applications, especially ones using Large Language Models (LLMs), use vectors to encode concepts, contexts, memories, reference sources and more. The size and complexity of such applications means first of all that massive amounts of vectors need to be stored and updated very efficiently. Secondly, the nature of the application requires that the database quickly provide the closest matching vectors in response to any query, based on a given measure of similarity.
