The search only for documents is outdated. Users who have already adopted a QA approach with their personal devices, e.g., those powered by Alexa, Google Assistant, Siri, etc., are also appreciating the advantages of using a “search engine” with the same approach in a business context. Doing so allows them to not only search for documents, but also obtain precise answers to specific questions.
What if you didn’t have to painstakingly sift through your spreadsheets and documents to extract the relevant facts, but instead could just enter your questions into your trusty search field? This is optimal from the user’s point of view, but transforming business data into knowledge is not trivial. It is a matter of linking and making all the relevant data available in such a way that all employees—not just experts—can quickly find the answers they urgently need within whichever business processes they find themselves.
With the power of knowledge graphs at one’s disposal, enterprise data can be efficiently prepared in such a way that it can be mapped to natural language questions. That might sound like magic, but it’s not. It is actually a well-established method to successfully roll out AI applications like QA systems in numerous industries.
Constructing a knowledge graph that integrates unstructured, semi-structured and structured data and then being able to query it with natural language to quickly obtain concise and comprehensible and fast answers is a technologically complex challenge. PoolParty and The QA Company have harmoniously integrated their compatible technological stacks to allow their customers to easily accomplish this task. Poolparty offers a rich collection of tools to enable the construction of knowledge graphs out of unstructured and structured data, while QAnswer offers a technology to access knowledge graphs via natural language.
