Changing the face of Contract Analytics using AI and ML

AI & Contract Analytics

The world is going through a lot of advancements in technology and making a huge impact on how business is being conducted and how organizations are adapting to these new technologies. A lot of human-intensive tasks are being fully automated ever since Artificial Intelligence and Machine Learning have come into usage.

we are seeing routine and mundane tasks being automated with the help of RPA (Robotic Process Automation), a lot of customer support functions getting automated with the help of Voice BOTS. It is not very far that we will witness wide usage of a Robot taking instructions from a recognized human voice and perform a business transaction on the fly.

Still, Departments like Sales, Procurement, Legal, Human Resource across organizations who are constantly handling Customers, Vendors, Employees are not making full use of the latest technologies like AI and ML in solving their day to day business challenges. Most of these have adapted to automation in the work they perform. For example, if you consider a procurement department entering into agreements with different vendors they have probably used technology in automating their contract management process like drafting a contract, sharing the draft with stakeholders for reviewing and redlining, negotiating contract terms and finally authoring the contract with a digital signature. 

However they might have not considered understanding different executed contracts, are there any deviations in them with respect to language and terms compared to the standard templates being used across the organization, how many contracts have a auto-renewal clause that need to be paid attention to, how many have penalty or damage clauses, which contracts are expiring in the next 30, 60 and 90 days and so on.

There are several reasons why organizations might have not considered or considering such needs as most organizations have executed paper-based contracts in the past and stored as scanned pdfs or images in various repositories or organizations have just considered using automation for managing the contract process but not for analyzing the key information inside the executed contracts. Another factor is that there is also usage of third party paper along with organization standard templates.

Added to the above most of the standard contract life cycle management solutions focus on the contract management process and not on contract analysis and insights.

Looking at this scenario and understanding the actual need of understanding and analyzing the key information from executed contracts, agreements, and other documents and bringing useful analytics and insights we have conceptualized and designed a powerful AI and ML based Contract discovery and Analytics Platform called Smart Contract Analytics (SCA).

Here are some of the key features of the SCA Platform
  1. SCA is powered by AI, ML along with underlying NLP making it a solution to analyze any type and format of documents.
  2. The Platform is completely SaaS-based on AWS making it flexible to use, easy to onboard and adhering to AWS security guidelines.
  3. The platform uses advanced ML models to train the machine to understand any document.
  4. Has the ability to extract key clauses, Metadata and also perform Metadata and Meta field-level search.
  5. The platform has the powerful ability to compare two executed agreements to see any differences at clause level and can also compare any executed agreement with the standard template to see any deviations visually.
  6. The platform works as a layer on top of any CLM system used by organizations and integrates the extracted metadata with the help of open APIs.
  7. The platform also has standard connectors with several data repositories like Dropbox, Box, Share Point, Google Drive, AWS, etc to discover the contracts and agreements and bring them to one repository and automatically segregate/classify them as MSA, NDA, SOW, etc.

Should you be interested to take a glance at the product or need more information please reach out to or refer to

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