Natural language processing and Semantic Analysis Powered Intelligence


Natural language processing and Semantic Analysis Powered Intelligence


Semantic Analysis Powered based on Azure ML algorithms to develop insights useful to your business

This application is available only in Italian, English.

What is Semantic Analysis?

Semantic analysis is an automated process of deriving high-quality information from text.

OAKS SAPI solution

OAKS offers SAPI, a solution based on Azure Machine Learning algorithms to analyze structured and unstructured data.

The solution can be used for analytical purposes like:

  • Sentiment analysis(Empathy, Dissatisfaction, Satisfaction categories etc)
  • Influencer identification
  • User contagion
  • Fake news detection
  • Web crawler (indexing)
  • Summarization (both extraction and abstraction)
  • AI-powered chatbot
  • Document tagging
  • Semantic Categorization
  • Keyword, named entities and topics extraction
  • Business categorization
  • Competitor & Partners identification

Business value of SAPI:

  • Saves time and labor costs by automating manual work, minimizing errors
  • Ensures services based on analyzing big amount of text data
  • Mitigates risks of not receiving crucial correct information at the right time
  • Helps making smart decisions on what is fraud, what is risky and what is relevant for business

Use cases:

  • Automatic customer request sorting by type, complexity, priority, or profitability, and further passing them on to sales people for immediate actions;
  • Improvement of clients satisfaction by immediate detection of pain and gain points and consequent definition of action plan
  • Quick acquisition of relevant data from web and databases, to speed up workflows and management;
  • Risk management: semantic analysis technology enables complete management of thousands of heterogeneous sources, and provides the ability to link together information and be able to access the right information at the right time;
  • Fraud detection through claims investigation: The majority of information in jurisprudence is collected as text. Insurance companies use text mining technologies by combining the results of semantic analysis with structured data to prevent frauds and swiftly process claims.