Nia Contracts Analysis

Nia Contracts Analysis utilizes Advanced Machine Learning techniques such as Deep Learning and Semantic Modeling to transform the process of analyzing and reviewing contracts. The application identifies pre-defined legal clauses in contracts and also determines whether the content in a certain clause is contentious or indicates risk in the given context. By doing so, Nia Contracts Analysis prevents losses and eliminates contracts’ inefficiencies

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Features


The application ingests the desired contracts to be reviewed, creates and learns from semantic models, classifies clauses into categories guided by its SME-trained knowledge base, and determines the contract’s clause status based on context. Users can query contracts through a natural language interface application which could be a chatbot capable of identifying user’s intent speeding up the contract review process.

  • Machine Learning features
    Natural Language Interface enabled query response

    • Users can configure themes based on queries
    • Users can review machine tagged data
  • Knowledge transfer
    The architecture of system, is provisioned to integrate with pre-trained models in the domain, by process called transfer learning, leading to superior accuracy

  • Progressive learning
    In addition, the network progressively learns (or self-learns) with human corrections or inputs

  • Language independence
    The underlying representation of language in a numeric form called word embedding not only facilitates it computability, but also makes it independent of the natural language

  • Other Features

    • User’s intent identification
    • Semantic Analysis
    • Context based analysis
    • Extensibility to different types of contracts

 

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Nia Contracts Analysis

Nia Contracts Analysis utilizes Advanced Machine Learning techniques such as Deep Learning and Semantic Modeling to transform the process...


 

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