The company was formed to develop technology that quickly finds the most relevant information in Big Data. Company’s focus is to introduce new and significantly improved approaches and solutions to search and classification.
The company’s product is a next-generation search tool that applies machine learning to search engine results and data sources to learn from users and returns personalized results based on the user’s feedback. This interactive engine can search multiple data repositories from multiple sources and iteratively apply Natural Language Processing and Machine Learning to user feedback to immediately provide results in a prioritized order. Rinalogy Search quickly provides users with only the relevant information they are looking for.
A standard process in any search technology is based on a user entering a query written in Boolean language that returns results. If after scrolling through the results (sometimes pages of results) the user is not satisfied with the information returned, the user modifies the query and repeats the process. Existing search technologies do not create models during the user session which learn from customer feedback and generate results.
To find the right results, the query often must be sophisticated, and it is not easy to express it in Boolean language, which is limiting the users. This is particularly important if there is a need to find any or all relevant information when searching Big Data. This need exists in industries such as consulting, legal, law enforcement, healthcare, financial services, academia, and others.
Another problem is that those who use several data sources need to search each one independently or create and index a collection of data to search from all data sources, requiring effort and time to complete.
Additionally, top results have highly correlated and overlapping content, causing the end-user to have to read through volumes of results to isolate nuances and find what they are looking for.
Product provides users the ability to quickly collate related content in an intuitive interface. Users begin a search by typing a query, and a model is built, in real-time, based on user feedback and the content of the results. The model allows the user to hone in on a topic, and through an iterative process, drill into their desired level of granularity.
Additionally, Rinalogy Search will curate and summarize the search results into an auto-generated collection of references to the underlying data sources. The power of Rinalogy Search is not limited to public content, as businesses can configure their data sources to include private search engines, unstructured data, and data fragments across their internal network via its robust set of prebuilt connectors.
Product provides users the ability to quickly collate related content in an intuitive interface. Users begin a search by typing a query, and a model is built, in real-time, based on user feedback and the content of the results. The model allows the user to hone in on a topic, and through an iterative process, drill into their desired level of granularity.
Additionally, Rinalogy Search will curate and summarize the search results into an auto-generated collection of references to the underlying data sources. The power of Rinalogy Search is not limited to public content, as businesses can configure their data sources to include private search engines, unstructured data, and data fragments across their internal network via its robust set of prebuilt connectors.