There are a lot of AI companies out there utilising the power of Natural Language Processing and Machine Learning for augmenting intelligence in managing operations, and often it’s hard to understand what help exactly your company needs.
So how are we different?
We specialise in helping companies with complex products and services, hence specialised taxonomy, where out of the box solutions simply don’t work. We improve their operations in providing real-time* service intelligence in areas as customer service, procurement and sales.
Still unclear? Ok.
For example, if you used Siri or Alexa and asked them a question how to fix your machine pump model XYZ123, it wouldn’t have a clue. That’s because it’s trained on generic, widely available data and not your company’s specific taxonomy; abbreviations, product names etc.
We, on the other hand, train our models by ingesting your company’s data and teaching our Machine Learning models relations and links between different concepts, your tribal internal company knowledge. Thanks to NLP (Natural Language Processing), our system can understand the meaning and context behind the words, just like a human who read all the available company docs would. We ingest all unstructured data which Untrite AI has an access to; it can be service tickets, manuals, Sharepoint documents, pdfs, excel files, technical drawings with metadata etc.
Untrite AI does not work like a standard enterprise intelligence platform so it doesn’t use keywords. You don’t need to know exactly what you’re looking for but you can describe a problem or an area of interest you’d like to see all the relevant information. Just like you would ask your human colleague to help you solve the problem.
One of the very common problems companies face is lack of unified taxonomy. Many of our manufacturing and engineering clients grow through acquisitions and often, compartments of the machines which were previously made by a different company were called something else, than a parent company it’s calling it. Nobody really takes time to manually unify the taxonomy in knowledge database, and even if they tried, it quickly would get outdated.
Experts being in the company for years and holding tribal knowledge will know the relation, but the newcomers may not. AI will find this relation automatically and will show you that “wire break 235 xys” is the same thing as “wire cable 678 xys”.