IBM - Sales Automation Solution – New

Company: IBM, Armonk, NY
Company Description: IBM is a values-based enterprise of individuals who create & apply technology to make the world work better. Today, more than 400,000 IBM employees around the world invent and integrate hardware, software and services to help forward-thinking enterprises, institutions and people succeed on a smarter planet.
Nomination Category: New Product & Service Awards Categories
Nomination Sub Category: Sales Automation Solution – New

Nomination Title: New Generation of Legal Support

Which will you submit for your nomination in this category, a video of up to five (5) minutes in length, explaining the features, functions, benefits, and results to date of the nominated new or new-version product or service, OR a written essay of up to 650 words describing the same? (Choose one): An essay/case study of up to 650 words

The Q2C RFP Analyser or QRA is a template-based and ‘continuous learning’ cognitive tool for analysing the terms and conditions in a request for proposal (RFP) document. QRA is a first of a kind cognitive application that would revolutionize the way we work with the Legal team with artificial intelligence. It is injecting AI in Legal as it helps automate the assessment of terms and conditions in document through augmented intelligence approach.

The tool aims to solve the main challenges faced by IBM sellers, legal and Contract & Negotiation (C&N) professionals when analysing the terms and conditions found in request for proposal documents. The tool is powered by AI technologies such as IBM Watson and a custom-developed NLP text extraction algorithm with an IBM Cloudant non-structured database at the backend. The user interface is built using Angular and Node JS.

As an illustration, when a government body issues RFP, an IBM seller needs to read the tender specs and understand its scope, which can come in hundreds of clauses. He would engage legal, C&N and other colleagues to thoroughly comb and analyze the terms and conditions so that IBM can respond appropriately to the tender.

During this process, the seller closely works with a Legal or C&N professional who needs to manually asses each clause and generate the list of key issues. This work often comes at the last minute and could be critical for the business before deciding whether to participate in the bidding. Nonetheless, the new documents are often similar to previous tenders, which would make the work repetitive.

QRA is a template-based document analyzer system. The tool could perform custom extraction and clause analyses in a specific domain. Each domain collection should have a mother template, which is basically a pool of paragraphs or clauses that frequently appear in the domain.

We have initiated the project for analyzing RFP documents coming from IT tenders issued by government authorities. Through its augmented intelligence capability, QRA learns from the pool of clauses belonging to the domain-specific ‘mother template’; so the next time a new RFP document from government authority becomes available, the tool could automatically analyze similar clauses within minutes.

In a document containing 562 clauses, within 2 minutes and high degree of confidence (>90%), QRA identifies that the majority or 325 clauses are similar to template clauses. QRA then auto generates the list of key issues that have previously been associated with the template clauses, avoiding unnecessary repetitive works. Through this approach, the team could now avoid performing repetitive manual analysis of clauses found to be similar with templates, especially if they are found to be pre-approved clauses. Instead, the team could straightaway shift their focus to sections that are different.

For an average contractual document, this process of analyzing the terms and conditions would be significantly reduced from 4 hours if it were to be done manually by an experienced legal or C&N professional to just under 2 minutes by using QRA. Hence, depending on the document complexity and their quantity, the savings delivered by QRA quite significant.

Through an augmented intelligence approach, QRA could help IBMers in performing critical tasks efficiently by automatically analyzing a document within minutes instead of hours or days. Through its cognitive and natural language processing capability, the QRA intelligence platform will improve with more usage overtime, helping us to focus more on the critical tasks ahead.

This project gave birth to the New Generation of Legal Support!

QRA is the first-of-a-kind AI application that directly helps IBM Legal / C&N to automate the assessment of terms and conditions in document through augmented intelligence approach. It created a new era of AI Support! Beyond legal domain, the tool could be scaled to other domains and countries!