The Excellence
Directory Platform Template

A managed service and tooling offering from Instaclustr that helps teams operate and optimize vector databases for GenAI and Retrieval-Augmented Generation (RAG) workloads, providing expertise and infrastructure management for production deployments.

Elysia is an open-source, decision-tree-based agentic system built on top of Weaviate that orchestrates tools and vector-search workflows, demonstrating how to build complex AI agents that leverage a vector database as a core component.

Verba is a community-driven, open-source Retrieval-Augmented Generation (RAG) application that provides an end-to-end, user-friendly interface for building RAG workflows on top of a vector database, showcasing practical semantic search and retrieval patterns with Weaviate.

DataRobot Vector Database is a managed vector store capability within the DataRobot AI Platform that allows users to create, register, deploy, and update vector databases for AI workloads, including RAG and semantic search. It integrates with NVIDIA NIM embeddings and supports both built-in and bring-your-own embeddings for building production-grade vector search solutions.

A premium vector database capability within the DataRobot Generative AI platform that stores chunked unstructured text and their embeddings for retrieval-augmented generation (RAG). Users can create vector database objects, connect supported data sources from the DataRobot Data Registry, configure embeddings and chunking, and attach these vector databases to LLM blueprints in the playground to ground model responses in proprietary data.

A Google Cloud reference architecture demonstrating an end-to-end two-tower retrieval system for large-scale candidate generation that uses Vertex AI and vector similarity search concepts to learn and serve semantic similarity between entities.

HelixDB is a powerful, open-source graph-vector database built in Rust, designed for intelligent data storage for Retrieval-Augmented Generation (RAG) and AI applications. It combines graph database features with vector search, making it directly relevant to AI and machine learning workflows that require vector data management.

LangChain is an open-source framework that integrates with various vector databases, including Pinecone, Weaviate, and Chroma, to facilitate retrieval-augmented generation (RAG) and advanced AI workflows.

Neo4j is a graph database that has added vector search capabilities, providing unique and effective approaches for retrieval augmented generation (RAG) and other AI applications.

Qdrant is a dedicated vector database and similarity search engine supporting advanced filtering and efficient retrieval, suitable for faceted search and retrieval-augmented generation. It offers self-hosted and cloud deployment options, making it highly relevant for vector search applications.

RETA-LLM is a toolkit designed for retrieval-augmented large language models. It is directly relevant to vector databases as it involves retrieval-based methods that typically leverage vector search and vector databases to enhance language model capabilities through external knowledge retrieval.