What is a real-world example of vector search?
eBay is an excellent example of a company using vector search to provide semantically correlated search results. Their vector search engine allowed eBay to increase search result accuracy by almost 100%.
Are vector search engines scalable?
Top-grade vector engines are flexible, scalable, and easily customizable. They are easy to integrate and require simple maintenance. If you’re dealing with large data sets, a vector engine can easily handle the load across multimedia platforms, e-commerce websites, etc.
Are there free open-source vector engines?
Yes, you have a selection of free vector search solutions to choose from, including:
- Jamf Protect – Apple device management and IT security;
- Txtai – AI-powered semantic search application builder;
- Qdrant – vector database for AI apps;
- UForm – Mid-Fusion-based semantic neural network;
- Vearch – a system for distributed vector retrieval.
Can all industries use vector search?
At the moment, vector search is most popular with content-heavy websites, streaming services, and e-commerce platforms. However, it can be beneficial for any business organization managing huge volumes of data and needing advanced search capabilities.