Algolia NeuralSearch Merges Vector Database and Keyword Technologies
The new AI-powered search engine aims to deliver highly accurate results, enhancing user experience and revenue conversion
Image credit: Algolia
Overview
Algolia, a leading search-as-a-service provider, announced the launch of Algolia NeuralSearch, an AI-powered search engine that combines vector database search with traditional keyword search. This innovative approach aims to improve search accuracy and enhance user experience for over 17,000 organizations, including Walgreens, Under Armour, and Petsmart.
In September 2022, Algolia acquired Search.io to expand its search capabilities by adding new vector search functionality to its existing keyword search technology. The result, Algolia NeuralSearch, promises highly accurate search results by leveraging the strengths of both approaches.
Vector databases have become increasingly essential in AI deployments, providing an optimized data repository for machine learning operations and data queries. Algolia's "secret sauce" lies in how it manages mathematical embeddings, or vectors, to accelerate query performance. The company's neural hashing technique distills vector similarities into binary forms that can be stored in the Algolia index for rapid query response.
The combination of keyword and vector search ensures optimized results, reducing instances of zero-result queries by 70% for early users. Organizations have also reported up to a 20% increase in revenue conversion.
Algolia's ambitions for its vector database technology extend beyond search. CEO Bernadette Nixon hinted at an upcoming release that will enable vector embeddings to work inside common SQL databases as just another data type. This development would eliminate the need for organizations to deploy separate vector databases alongside traditional SQL-based databases to power larger applications.
With Algolia NeuralSearch, the company is revolutionizing AI-powered search by merging vector database and keyword technologies, improving search accuracy, and ultimately delivering better user experiences and revenue conversions for organizations. Source