Contract Data Extraction Benefits and a Short “How-To” Do It with AI
By Jean Mauris Co-founder and Head of Product at Avokaado
Every company has hundreds or thousands of contracts: partnership agreements, sales contracts, NDAs, employment agreements, and so on. Most of the time, these contracts are stored somewhere (in the best-case scenario, digitally) and are only looked at when changes are necessary or in case of audits and due diligence. But every organization can benefit from the business-related data hidden in all these documents. Let’s dive deeper into the case.
What are the benefits of contract data extraction?
Operational Efficiency
Reviewing contracts manually is time-consuming and prone to human error. Going through documents to figure out what data they contain can take hours. Automated data extraction streamlines this process, allowing for quick retrieval of essential information like payment terms, delivery schedules, and legal obligations. When contract data is properly extracted, it can help any team save tons of time when looking for specific things in contracts.
Risk Management
Contracts always contain clauses related to liabilities, indemnities, and warranties. Extracting this data helps organizations identify potential risks and manage them proactively. Understanding obligations and exposure can prevent legal disputes and financial losses. Every business unit can easily identify which risks they want to monitor inside their contracts, and when the data is extracted, it is a simple task to keep an eye on them.
Regulatory Compliance
If your organization operates in a highly regulated industry (like banking and finance or healthcare), you are probably subject to strict regulations that require adherence to specific contractual terms. Extracted data ensures that all regulatory requirements are met, avoiding penalties and maintaining good standing with governing bodies. It also gives you a complete picture of non-compliant clauses and terms so you can amend your contracts properly.
Financial Management
Contracts often dictate payment schedules, pricing, and penalties. Extracting financial data enables accurate forecasting, budgeting, and financial planning. It also ensures timely invoicing and payments, improving cash flow management. It is your only source of truth when it comes to financial terms and conditions. It can also show you information about renewals and terminations.
Strategic Decision-Making
Access to structured contract data allows you to analyze trends, negotiate better terms, and make informed decisions. For example, understanding common clauses across contracts can help standardize terms and improve negotiation strategies. Revealing contract data will show you patterns across different business units—patterns that you can use to automate some parts of the document management process.
Audit and Accountability
Having extracted data readily available facilitates internal and external audits. It ensures transparency and accountability, demonstrating that the organization adheres to contractual obligations and maintains proper records. Imagine you don’t need to gather thousands of documents for an audit, but instead have a table with all major contract data available at your fingertips.
Technology Integration
Extracted contract data opens up the possibility of integrating it into various business systems like CRM, ERP, and compliance tools. This integration fosters a cohesive ecosystem where contract terms directly influence operational processes. And again, contracts are your only source of truth you can trust, so having the ability to exchange contract data with other systems is crucial.
Data Analytics and Reporting
Last but not least, structured data enables advanced analytics, helping your organization identify patterns and gain insights. Reporting on contract performance, risk exposure, and compliance status becomes more straightforward and data-driven. You don’t need to go through all the documents to build reports; instead, you operate with data points.
How should you approach contract data extraction?
Now let's get much more practical. If you decide to get into contract data extraction, there are some things you need to be aware of so your initiative won’t die in vain. And of course, we are sharing an example of how to do it with AI (Large Language Models specifically) like ChatGPT, Gemini, or any other available on the market.
Step 1: Define the contract data points you want to extract
Every organization has different data points that they monitor. Some of them are common; some of them are very organization-specific. Before you do the real work with data extraction, you need to define which document types you want to extract data from. Make sure you involve different stakeholders in the process who are dealing with these contracts. Here are some examples:
Employment contracts
NDAs
Vendor agreements
Sales agreements
Partnership agreements
Each of these document types will have different data points. Some of them will be purely commercial (amount, payment terms, etc.); some of them will be legal (non-disclosure, termination, etc.). Make sure you discuss necessary data points with relevant stakeholders inside your organization.
Step 2: Experiment with prompting contract data
For each data point (or a group of data points), you should create the best possible prompt. For example, if you extract data from an employment agreement, you should ask, “Give me the first and last name of the employee in this employment agreement.” Be as specific as you can; it will help to get much better results. Run experiments using different documents with different sets of data to achieve the best results.
When designing a prompt, make sure that you guide the AI on how you expect to get a response. In the case of an employment agreement, you probably don’t want to have a long answer like, “An employee in this employment agreement is John Smith,” but instead you just want the answer to be “John Smith.”
Step 3: Run extraction at some scale (10–20% of total documents)
When you feel like your prompt design returns quality responses from the uploaded documents, run a test on a bigger scale. Try to upload 10% of all your target documents and contracts of the same type and ask to design a table out of the responses instead of just providing you the list. When this step is complete, you can proceed with extracting contract data from all of your documents.
Step 4: Store and update your data
When the data is extracted, it is crucial to have an overview of the data and the ability to update it when necessary. From a simple Excel table with all the main data points to platforms like Avokaado, you are free to choose whichever works best for you. But make sure that extracted data is available to all relevant stakeholders inside your organization.
Important
The steps above should be performed for every document type (every set of data points you want to extract) because there is not much similarity between a sales agreement and an employment agreement, for example.
How we do contract data extraction in Avokaado using built-in AI
Luckily, in Avokaado we have all of the steps above already built into the platform. It allows our customers to easily define document types as well as data points and run data extraction on autopilot. Here are some of the key opportunities:
No-code interface to define all the document types
In Avokaado, we provide a simple interface where you can define as many document types as you need and add all the data points (we call them smart fields) that you need to extract and monitor. Every document type can have multiple parties (businesses and individuals) as well as smart field sets.
Smart field sets are used to group different types of data points so you can review and share them separately. For example, legal terms are in one smart field set; commercial terms are in another. In terms of data points, you can define text (e.g., name, last name), long text (e.g., address, special terms), date (e.g., sign date, termination date), number (e.g., contract value, payment term), options (e.g., is there a probation period), and much more.
This no-code editor allows you to design contract data structures that fit your organization specifically.
Avokaado Document Type & Contract Smart Fields
Simple upload and data extraction
When all the document types with relevant data points are defined, all you need to do in Avokaado is just drag and drop contracts (in PDF, DOCX, EDOC, ASICE) and see the magic happening.
At Avokaado, we treat data sensitivity and privacy very seriously. Our model operates using pre-trained OpenAI LLM that operates in isolated instances, so AI doesn’t use any of your contract data. We also do not store any of the data outside of your Avokaado Workspace to make sure there are no possible data leakages.
When your documents are processed by Avokaado AI, you’ll be able to review all the extracted data, re-extract it if necessary, as well as edit it manually in case you notice some discrepancies. All done through a simple, user-friendly interface of your Avokaado workspace.
Avokaado AI Contract Data Exctraction
Data storage and overview
When all of your documents are processed, the next step in Avokaado Platform magic happens. We create a full list of all the extracted data points that you can review as a simple table. No need to go into every document to get insights of what is there; it is all available in our user-friendly view.
For your convenience, we also have the ability to modify the table view the way you see fit as well as export data to CSV so you can work with it the way you need. In Avokaado, you can also share different data sets with different teammates without sharing actual documents. It comes in handy when you don’t need to (or must not) share full information but just bits and pieces.
Avokaado Contract Data Registry
Parties registry on autopilot
Another feature we have as one of the Avokaado Platform cornerstones is the Parties Registry. Every contract your organization has contains a counterparty (either business or individual). When extracting your contract data, we analyze parties and organize them into a simple user registry that is available on demand for all Avokaado Workspace users.
Parties Registry allows you to browse all extracted documents (including document data) connected to a specific party.
Avokaado Parties Records view
Bonus - multi-language support
As a bonus, our pre-trained LLM model works pretty much with any popular language out of the box. Meaning that if you have a contract in German but want to extract all the data into your English version of the data registry, we will do it for you automatically.
If you want to learn more about contract data extraction or see the Avokaado Platform with AI capabilities in action, book a demo with our experts.
Avokaado offers a comprehensive contract lifecycle management platform that can streamline and optimize every stage of the contract management process. From automated contract creation to secure storage and compliance tracking, Avokaado provides the tools necessary to manage contracts efficiently and effectively. By leveraging Avokaado's user-friendly platform, businesses can reduce manual work, minimize errors, and ensure consistency across their contract management practices. To see how Avokaado can transform your contract management workflow, visit https://avokaado.io/ for more information, request a demo, or create a free account.
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