Weaviate is an open-source vector database designed to facilitate the development of AI-native applications by providing efficient storage and retrieval of vector embeddings. It combines vector search with traditional keyword search techniques, allowing for precise and contextual data retrieval across various data modalities. With integrations for popular machine learning models and support for hybrid search, Weaviate empowers developers to create applications such as semantic search engines, recommendation systems, and chatbots. Its cloud-native architecture ensures scalability and flexibility, making it a preferred choice for both developers and enterprises aiming to leverage AI in their software solutions.

Weaviate

weaviate

An open-source, AI-native vector database enabling developers to build and scale AI-powered applications with advanced data retrieval capabilities.

Haystack is an open-source Python framework developed by deepset that enables developers to create production-ready applications powered by Large Language Models (LLMs) and retrieval-augmented generation (RAG) pipelines. It offers a modular architecture, allowing integration with various AI models and tools, including OpenAI, Hugging Face Transformers, Elasticsearch, and more. Haystack supports tasks such as question answering, semantic search, and document retrieval, facilitating the development of sophisticated AI applications. Its flexibility and scalability make it suitable for both research and enterprise use cases.

Haystack

haystack

An open-source AI framework for building production-ready applications with Large Language Models (LLMs) and retrieval-augmented generation pipelines.

AI Agents Tagged with "semantic search"

Weaviate

Haystack