This code pattern explains how to create a platform to help insurance agents process claims. We use IBM Watson natural language processing capabilities to understand, classify, and retrieve information to reduce repetitive tasks. In turn, this allows the agent to tackle more creative and complex problems, and most customers receive answers to their questions faster with the help of a Watson-based virtual assistant. We create the virtual insurance assistant using Node.js and Watson Assistant. The assistant uses Watson Discovery to answer policy questions.

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Create and deploy custom annotation models without writing a single line of code. With our new IBM Watson Knowledge Studio free plan, developers can create custom annotator components and five machine learning projects using 5GBs of storage. And there's no time restriction to do so. Use both machine learning and rule-based approaches to create custom language models using a cloud-based application. The rule-based approach (currently experimental) gets results fast, while the machine learning approach helps the model scale.

As enterprise enters further into the digital age, data has become the strategic asset that knowledge workers, small or large, rely on to guide their decisions. However, managing such large volumes of data has exposed some unprecedented challenges for the enterprises. Enterprises have learned that the data that they hold, comes in a variety of formats, resides in different and distributed systems and is specific to the organization and its domain. Setting these challenges as the backdrop, IBM's Watson division has built solutions that not only allow for data connectivity but also the analysis of unstructured data and its customization to an enterprise domain. IBM Watson Explorer is Watson's flagship product for text analytics and discovery.

As enterprise enters further into the digital age, data has become the strategic asset that knowledge workers, small or large, rely on to guide their decisions. However, managing such large volumes of data has exposed some unprecedented challenges for the enterprises. Enterprises have learned that the data that they hold, comes in a variety of formats, resides in different and distributed systems and is specific to the organization and its domain. Setting these challenges as the backdrop, IBM's Watson division has built solutions that not only allow for data connectivity but also the analysis of unstructured data and its customization to an enterprise domain. IBM Watson Explorer is Watson's flagship product for text analytics and discovery.