Case study Insights Engine
Alexandria.Works brings accurate insights in unstructured content. The platform extracts information from large amounts of documents and texts. This capability and associated value are appreciated by Flanders Innovation & Entrepreneurship (VLAIO) and customers including Engie EMS and VLHORA.
Alexandria.Works developed a very efficient search and discovery tool for enterprises. The platform helps you to find more accurate information in unstructured data fast. It uses advanced Natural Language Processing (NLP) technology to inform the end-user with most relevant topical data, deeply embedded in the corpora fed to the system. Unlike other tools, there is no need of excessive time, money or other resources to prepare the input data (i.e. no ‘supervised learning’ in AI terms). This is enabled by the ‘Topical Facet’™. Today’s platform retrieves quasi-instantly all relevant documents from a query formulated in human language.
Going forward, Alexandria.Works extends its technology to zoom in on documents and extract truly relevant topics. The user will be empowered to fluently navigate through documents, topics and text snippets. When combined with Electronic Document Management systems, such as SharePoint, the embedded engine just works without the need to tag each and every document.
"iOmega grasps the essence fast and translates it in clear explanations."
Marc Vanderheyden, Alexandria.Works
Although the success of a consumer search tool as Google seems to indicate the opposite, the problem of accessing and exploring unstructured data is not a solved issue for organizations. There exists today a discrepancy in what the market can offer today and a real need for enterprises. The root cause is at technology level and Alexandria.Works changes that. With its data mining technology, the user really finds the information they are looking for, wherever that information is stored.
Alexandria.Works brings innovative technology. Its platform discovers all semantic relations in unstructured text at indexing time in a language independent way. No issues with synonyms or polysemy and no need for additional resources to prepare the input. After all, these extra resources prove unsurmountable in real life use cases. In a joint effort with iOmega we structured all innovative steps in well-written application file.