Hey HN,<p>At Mintplex Labs are building developer tools for AI applications. One area we encountered frustration was the use of Vector Databases like Pinecone, Chroma, QDrant, or Weaviate to "unlock" long-term memory and contextual answers. It is nearly impossible to manage this data when in use for production.<p>The craziest thing was how you cannot atomically CRUD any vectors in most of these vector databases. Let alone easily copy, clone, or migrate data or entire indexes without paying for re-embedding - among other things.<p>With VectorAdmin you get a database level UI with the ability to easily search for embeddings and atomically manage them on top of being a general tool suite for those using vector databases with LLMs.<p>Some things we have unlocked with Vector Admin:
- Upload data directly into the vector db via a text doc or PDF
- One click sync of entire existing vector databases
- Migrating entire db's to another provider to escape vendor lock in
- Ability to duplicate collections/namespaces to create dev-environments off production data at no cost
- Be able to finally reset a vector database (provider agnostic)<p>and soon, be able to detect "drift" in semantic search results and catch it early before your production system starts providing wild context snippets.<p>VectorAdmin is open-source or hosted and has a 3-day trial. We really want HN's feedback on the issues or problem you are having wrangling the actual data in a vector database while building any LLM application.