Results for “embeddings”

turbopufferNew

Vector + full-text search database built on object storage: cheap at scale, sub-10ms latency, used by Cursor, Notion and Linear.

ZepNew

Builds a living map of everything a user has told an AI agent over time — and how those facts connect and change — so the agent can pull up exactly the right context in under 200 milliseconds instead of re-reading an entire chat history.

Mem0New

Gives AI chatbots and agents a real memory — so they remember what you told them last week — instead of forgetting everything the moment a conversation ends, the way most AI apps do by default.

minimiNew

A quiet memory that watches what you're doing on your Mac so you don't have to explain it to Claude every time — your open tabs, documents, and calls become context Claude already knows, without ever leaving your computer.

TwelveLabsNew

Lets you search inside videos using plain English — like "find the scene where someone signs a contract" — instead of scrubbing through hours of footage or relying on manual tags someone forgot to add.

Nile

A Postgres platform for B2B apps. Unlimited databases, Always available with no shutdown, 1GB of storage (total), 50 million query tokens, autoscaling, unlimited vector embeddings

Rivestack

Managed PostgreSQL with pgvector optimized for AI workloads. The free tier includes 2GB storage, daily snapshots, 14-day point-in-time recovery, and a built-in SQL editor that converts search queries to vector embeddings.

Towhee

A Python module that encode unstructured data into embeddings.

ArcadeDB

Multi-model database supporting graphs, documents, key-value, time series, and vector embeddings with SQL, Cypher, Gremlin, MongoDB, and Redis API compatibility.

LanceDBNew

An open-source database built specifically to store and search the huge piles of images, text and embeddings that AI systems train on and search through.