Optimize RAG pipelines for LLMs by importing, experimenting, and deploying vectors
Accurate retrieval-augmented generation (RAG) platform
Experiment with different chunking and embedding
Refine vectorization strategy and improve LLM context
Pricing:
Vectorize.io is a platform engineered to optimize retrieval-augmented generation (RAG) pipelines for large language models (LLMs). It allows users to import data from various sources, experiment with different chunking and embedding strategies, and deploy real-time vector pipelines. This enables the creation of generative AI applications that enhance productivity and customer experiences by utilizing the collective knowledge from content management and collaboration tools.
- Fast, Accurate RAG Pipelines: Enables the creation of production-ready Retrieval-Augmented Generation (RAG) pipelines, ensuring your data is always up-to-date and accurately indexed.
- Three-Step Deployment: Easily unleash the power of Large Language Models on your data with steps to import, experiment, and deploy.
- Import Capabilities: Upload documents or connect to external knowledge management systems to extract natural language for use by your LLM.
- Experimentation Tools: Test a multitude of chunking and embedding strategies in parallel, using recommendations or selecting your own for optimal results.
- Real-time Deployment: Convert selected vector configurations into real-time pipelines that automatically update when changes occur to maintain accurate search results.
- Wide Integration: Out-of-the-box connectors to popular knowledge repositories, collaboration platforms, CRMs, and more, making it easy to turn organizational knowledge into generative AI.
- Top AI Platforms Support: Includes support for embedding models and chunking strategies from Hugging Face, Google Vertex, LangChain, AWS Bedrock, OpenAI, Microsoft Azure, Jina AI, Voyage AI, and Mistral AI.
- Automatic Index Creation: Automatically create and update vector indexes in your preferred vector database, making your data AI-ready.
- User-Friendly Interface: Designed to make the identification of optimal embedding models and vectorization strategies straightforward, offering a free trial to get started quickly.
- RAG Sandbox and Experiments: Features a sandbox for end-to-end testing and experimenting with different vectorization strategies to refine and enhance LLM context.
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Vectorize.io
Optimize RAG pipelines for LLMs by importing, experimenting, and deploying vectors
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