Corporate Discoverability
John was a great salesman. He got a hot lead but had only one day to prepare for the presentation. He quickly dived into the CRM to find any information that would help him sell. He found most of the documents that he was looking for, but he still lost the deal. He would have won if he knew that useful insights about the lead were recorded by a customer support specialist, business analysts, and a colleague in a different department. The ability to find documents that are useful to a user, but they have no knowledge of their existence, is called corporate discoverability. This functionality is enabled with a Natural Language Processing tool to read the content within an ECMS such as SharePoint and to understand the context of each document. Key word search alone simply can’t understand the relationships within documents to enable corporate discoverability.
IMPROVING FINDABILITY
The most common corporate challenge is finding information that you need. It might be a simple email lost in Outlook or a document that was created a year ago. Pingar enriches your knowledge assets to ensure easy document findability. We apply natural language processing methods to enable an Enterprise Content Management System to quickly locate information that you need.
PROVIDING DISCOVERABILITY
Corporate discoverability is a process when a Natural Language Processing tool is trained to find relevant content to populate your search inquiry. Pingar deploys knowledge structures that are enriched with alternative labels (a form of synonyms) and relationship identification functionality. These structures allow employees to discover content that they are unaware of, not only the specific content they are looking for. This enables multiple users to quickly discover the same content despite them having different ways to describe it.
Limitless Document Auto-Categorization Capabilities
Various research shows that approximately 25% of corporate data is structured within databases or similar systems. The other 75% of the corporate data is unstructured such as the many types of documents. It can contain sensitive information that must be protected, contracts that must be retained and documents that should be utilized. DiscoveryOne reads, analyzes, tags and categorizes unstructured data and therefore gives insights and visibility over your data. It simplifies content management, increases security and simplifies retention practices.
Using Artificial Intelligence to Drive a Change
Pingar uses supervised learning, which means a user can provide a sample set of documents that represent a particular category of documents to be created. Pingar DiscoveryOne reads and analyses the sample documents and is then able to recognize additional documents for the designated category. Pingar analyzes the sample documents to identify patterns that reflect the category and creates them as rules. Each rule is given a weight depending on how important it is. Then artificial intelligence will use these rules to identify documents that should belong to a category. It will also identify new rules to advance itself.
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