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PoolParty + QAnswer

Have a conversation with your data!
Organizations are investing in automated solutions for organizing, accessing and analyzing their data. The ultimate goal is to give non-expert users fast access to enterprise data and provide them with answers to their questions. This is achieved by constructing a natural language interface over enterprise data integrating unstructured, semi-structured and structured data that is able to quickly provide concise and comprehensible answers to user queries.

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“…by 2020, 50% of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.”

Why Question-Answering Engines?

The search just for documents is outdated. Users who have already adopted a question-answering 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.

Question-answering (QA) systems respond to questions that someone can ask in natural language. This technology is already widely adopted and now rapidly gaining importance in the business environment, where the most obvious added value of a conversational AI platform is improving the customer experience. Another key tangible benefit is the increased operational efficiency gained by reducing call center costs and increasing sales transactions. More recently we have seen a strong developing interest in in-house use cases, e.g., for IT service desk and HR functions. 

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.


A Strong Partnership

Approach Architecture
Together, the PoolParty Semantic Suite and QAnswer offer a knowledge graph-centric enterprise solution for querying your enterprise data in natural language that is multilingual, explainable, accurate, and scalable. 


Learn more about the methodology, system architecture, and technologies involved in our white paper.