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.
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.
Natural Language Interface enabled query response
The architecture of system, is provisioned to integrate with pre-trained models in the domain, by process called transfer learning, leading to superior accuracy
In addition, the network progressively learns (or self-learns) with human corrections or inputs
The underlying representation of language in a numeric form called word embedding not only facilitates its computability, but also makes it independent of the natural language
User’s intent identification
Context based analysis
Extensibility to different types of contracts
Traditional processes for analyzing and managing contracts is resulting in loss of revenue, productivity, and increased risk. Nia Contracts Analysis changes it all
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