The decision to build or buy is a common step in the implementation of advanced technology solutions. In Part 1 of this article, you learned how AI can help you analyze contracts, how traditional AI training works, and three downsides of building traditional AI training for contract analysis. In this part 2, you will learn how ThoughtTrace’s pre-trained contract analysis software works on day one, and why application leaders facing AI implementations have confidently moved in this direction
New Approaches to Contract AI Training
The advantages of contract management software are vast, and AI-based systems are even more powerful and efficient. However, traditional methods for training AI models take too much time and are typically based on too little volume and variety when designed within the silo of a single entity. Proper AI training requires expert data science skills, dedicated time, startling contract volume, deep learning technologies, and endless varieties of data consistently maintained – one or more of which your company may not possess.
Novel approaches are necessary to speed up the process and provide greater contract diversity and quantity. ThoughtTrace, by comparison, takes a unique approach to model development fueled by supervised AI and community-driven insights that we believe to be a true differentiator for our customers.
Download the Whitepaper:
ThoughtTrace Model Development – The Strategy Behind the World’s Most Accurate Contract AI Software
Written by ThoughtTrace CTO, Joel Hron
Developing Pre-Trained AI with Community-Driven Data Sets
When the training data consists of similar, inappropriate, or simply poor-quality contracts, the resulting AI model will be similarly flawed. It’s the old concept of “garbage in, garbage out; “the training data set must contain many high-quality contracts of various types to produce high-quality results. This cannot be overstated – data plays the most critical role in developing valuable, effective machine learning and AI systems (read why).
One approach to diversification of contract input is the use of community-driven data sets. That is, instead of feeding the system contracts from a single entity, contracts and documents from thousands of different companies are fed into a community pool data set. This pool, comprised of a large number of diverse contracts, is then used to pre-train the AI model. The AI does not have to rely on a limited number, type, or style of contracts from a single company; it benefits from using a large number of contracts from a wide variety of companies.
Employing Subject Matter Experts
The raw data is nothing without a model to form context around the patterns of characters and intent of the clauses. Even the best data sets are useless without scrupulous labeling and training by subject-matter-experts in tandem with a team of data scientists fine-tuning the algorithm’s attention to details.
For this reason, ThoughtTrace employs a roster of Subject-Matter-Experts (SMEs) with direct experience in the legal, contractual, and business elements to analyze the contracts fed into the system. This experience and knowledge is applied to ensure accuracy and consistency. The additional information about how contracts are utilized in specific industries and instances has a significant impact on content extracted from each agreement
How ThoughtTrace Improves Contract AI Training
ThoughtTrace employs both innovative approaches in its contract AI. The proprietary use of community-based AI models combined with valuable input from industry-savvy SMEs create more accurate contract analysis models in a fraction of the time and cost of in-house trained solutions. ThoughtTrace customers get the expected benefits of AI-based contract analytics software along with a significantly faster time-to-value and a more accurate model, ending the build versus buy debate.
Accelerates the Process
Unlike traditional toolkit systems that require months of AI training, ThoughtTrace works on day one, right out of the box. According to research firm Cognilytica, close to 80% of the time spent developing an AI project is focused on collecting, labeling, and inputting data to train the system. With ThoughtTrace, all this work is done upfront. This saves you the time and effort of doing this complex work – and lets you put your AI-based document understanding & contract analytics software to work immediately.
After you upload your documents, ThoughtTrace will intelligently read, classify, and categorize them for you, and then use them to create a more precisely suited model for your business.
Creates a Large Data Set
ThoughtTrace can leverage the entirety of our customer data sets in a secure and protective way, unlocking exponential increases in the amount of data available to use to inform and improve model performance. To date, ThoughtTrace’s community AI has processed millions of contracts and billions of words to train its AI model. That is a considerably larger data set than even the largest business could feed into the system – and the resulting sophisticated, intelligent model is there on day one, ready for you to use.
Delivers Data Diversity
When training an AI system, the variety of data entered is equally as important as the volume. Models need to be built from diverse types of contracts so that it will perform well in all possible situations. Unfortunately, most businesses utilize only a limited number of contracts, which does not provide the diversity necessary for full-featured contract analysis.
Variety is where ThoughtTrace’s community AI really shines. The ThoughtTrace model includes all types of contracts from various organizations, more than a typical business is likely to generate. ThoughTrace’s wide base of contract types mitigates against any biases present in small data sets and prepares the model for any contingent situations.
Fine-Tuned for Accuracy
Building on the wide base of contract types fed into the AI model, ThoughtTrace employs a team of SMEs, all with direct legal and contractual experience key to client’s industries. These SMEs enhance and fine-tune the data fed into the AI model to ensure the highest possible degree of accuracy.
The experts at ThoughtTrace spend considerable time optimizing the management of training data to mitigate model biases, scrutinize model statistics to mitigate model performance degradation, and perform maintenance tasks that are necessary to ensure consistency and accuracy. The use of SMEs, combined with an ever-expanding community-based data set, results in a continuously learning model and improving itself.
ThoughtTrace Contract AI: It Just Works
ThoughtTrace’s approach to AI training has proven successful with a wide variety of clients by building domain-specific solutions to answer complex questions in record time. Combining community-based AI training with fine-tuning by SMEs speeds up the learning process and provides more accurate results. As a client, Great Western Operating Company, LLC, noted after first implementing the ThoughtTrace platform: “IT JUST WORKED!”
