What is Vectorize?
Vectorize is a fast, accurate, and production-ready AI platform that enables users to turn their unstructured data into perfectly optimized vector search indexes, purpose-built for retrieval augmented generation.
Features of Vectorize
- Import data from anywhere in your organization using out-of-the-box connectors to popular knowledge repositories, collaboration platforms, CRMs, and more
- Automatically create and update vector indexes in your favorite vector database
- Leverage the collective knowledge from content management, file systems, CRMs, collaboration tools, and more to create productivity-enhancing copilots and innovative customer experiences
- Use Vectorize's recommendation or choose your own chunking and embedding strategies in parallel, quantifying the results of each
How to use Vectorize
- Import: Upload documents or connect to external knowledge management systems, and let Vectorize extract natural language that can be used by your Large Language Model (LLM).
- Evaluate: Vectorize will analyze multiple chunking and embedding strategies in parallel, quantifying the results of each. Use our recommendation or choose your own.
- Deploy: Turn your selected vector configuration into a real-time vector pipeline, automatically updated when changes occur to ensure always-accurate search results.
Pricing
Vectorize offers a free trial, and users can schedule a demo to learn more about the pricing plans.
Helpful Tips
- Use Vectorize to create generative AI applications to power your customer experiences in hours, not weeks.
- Leverage the power of Large Language Models on your data in 3 easy steps.
- Stay up-to-date on the latest trends, tips, and insights in the gen AI world to empower your business growth and increase productivity.
Frequently Asked Questions
- What is Retrieval Augmented Generation (RAG)? Retrieval Augmented Generation (RAG) is a technology that enables users to turn their unstructured data into perfectly optimized vector search indexes, purpose-built for retrieval augmented generation.
- How do I build a better RAG pipeline? To build a better RAG pipeline, users can follow the three easy steps: Import, Evaluate, and Deploy.
- What is Prompt Engineering? Prompt Engineering is a technique used to optimize the input prompts to Large Language Models to improve the accuracy and relevance of the output.
