Amazon Web Services > 实例探究 > Using Machine Learning on AWS to Eliminate Manual Contract Reviews

Using Machine Learning on AWS to Eliminate Manual Contract Reviews

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公司规模
SME
地区
  • America
国家
  • United States
产品
  • LinkSquares software
  • AWS
  • SFL Scientific machine learning solution
技术栈
  • AWS
  • SQL
  • Natural Language Processing (NLP)
  • Artificial Intelligence (AI)
实施规模
  • Enterprise-wide Deployment
影响指标
  • Productivity Improvements
  • Cost Savings
技术
  • 分析与建模 - 机器学习
  • 分析与建模 - 自然语言处理 (NLP)
适用行业
  • Software
  • Professional Service
适用功能
  • 商业运营
  • 销售与市场营销
用例
  • 计算机视觉
服务
  • 数据科学服务
  • 云规划/设计/实施服务
关于客户
LinkSquares is an industry disruptor in contract review, providing high-growth companies with a suite of tools to complete fast and systematic legal reviews of executed business agreements. The company was founded by individuals who experienced the painful reality of reviewing existing legal contracts firsthand while their previous employer underwent an acquisition. They identified a gap in the market for a software solution to help companies mine for information in existing contracts, and thus, LinkSquares was born. The company is focused on post-signature contract analysis and does not deal with anything pre-signature. They built their software as a service (SaaS) offering on AWS to quickly migrate companies from their existing storage solutions and enable them to understand what they agreed to in their contracts.
挑战
Companies experiencing rapid growth often lack the bandwidth to track each line of every contract, service agreement, or legal document before it’s executed. Even in the most carefully reviewed agreements, some information is forgotten as soon as the contract is signed. Once the business has matured and due diligence projects arise (for example, when a law changes or an acquisition takes place), companies must conduct detailed reviews of all signed contracts and identify specific terms within them. LinkSquares’ founders experienced the painful reality of reviewing existing legal contracts firsthand while their previous employer underwent an acquisition. The team identified existing software solutions helping companies efficiently address the pre-signature workflow: contract creation, terms negotiation, and internal workflow. However, the industry lacked a software solution to help companies mine for information in existing contracts.
解决方案
LinkSquares turned to SFL Scientific, a data science consulting firm, AWS Partner Network (APN) Consulting Partner and AWS Machine Learning Competency Partner, to build a scalable solution for identifying and classifying legal language. SFL Scientific used Natural Language Processing (NLP), an Artificial Intelligence (AI) method helping computers understand and interpret human language, to build its machine learning algorithm. Implementing the algorithm enabled LinkSquares’ software to extract key terms from a document and tokenize these terms into predefined categories. Upon deployment on AWS, the algorithm ran the code on demand. Whenever a document was uploaded, the machine learning code automatically launched. The NLP algorithm developed by SFL completely revolutionized the post-signature contract review process for LinkSquares. The machine learning code enables the LinkSquares software platform to automatically run code on thousands of documents in seconds.
运营影响
  • LinkSquares was able to focus its resources on optimizing products rather than maintaining infrastructure.
  • The company was able to scale and improve accuracy with the help of the machine learning solution developed by SFL Scientific.
  • The solution provided by SFL Scientific completely revolutionized the post-signature contract review process for LinkSquares.
数量效益
  • The machine learning code enables the LinkSquares software platform to automatically run code on thousands of documents in seconds.
  • Every result showed an exponential improvement in time spent reviewing each document.
  • Improvement in tagging accuracy compared to the human auditors.

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