A cloud-native vector database, storage for next generation AI applications
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Updated
Jun 7, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
AI + Data, online. https://vespa.ai
Distributed vector search for AI-native applications
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
OSINT Platform - Provides image analysis, digital footprints, video transcription and more. Retrieval Augmented Generation (RAG) capable platform
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
An embedded vector database designed to run on edge devices. Lightweight and fast with HNSW indexing algorithm.
🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.
cuVS - a library for vector search and clustering on the GPU
Redis Vector Library (RedisVL) interfaces with Redis' vector database for realtime semantic search, RAG, and recommendation systems.
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Resume Matcher is an open source, free tool to improve your resume. It works by using language models to compare and rank resumes with job descriptions.
The open-source tool for building high-quality datasets and computer vision models
Website for the Weaviate vector database
A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.
Build LLM-powered applications in Ruby
Music streaming application using nextjs
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
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