Transforming Contracts into Contracts Intelligence

Contracts are complex and unstructured, and the data they contain is similarly complex and unstructured. To have accurate, actionable, and accessible information on your contracts, you cannot simply use automated technology or an army of people to input data into a database. Extracting contract data and transforming it into Contracts Intelligence requires sophistication and process.

Pramata employs a proprietary technology enabled process to take our customers contractual documents and give them an ongoing stream of Contracts Intelligence. This process begins with the end in mind. We designed our process by starting with the business problems people solve with contract information. With this in mind, we then applied a combination of proprietary technology and experienced lawyers to ensure we produce Contracts Intelligence that is both useful and reliable.

Sample Contracts Intelligence report

Automated Data Extraction

Some contractual information can be exactrated using pure automation. Some information requires experienced lawyers to review and interpret complex legal clauses. We understand which information can be automated and which requires a review from experienced professionals. As the first step in our process, all documents pass through Pramata's automated Optical Character Recognition (OCR) technology to capture basic information. This automated extraction step allows our professionals to focus their attention on the most complex contractual terms and information.

Manual Data Extraction

Because contracts are negotiated and contain nuanced information, extracting data from them cannot be entirely automated. The most important, and often the most complicated, information locked in contracts requires experienced professionals to review the contract, interpret meaning, and input data. With the help of our extraction technology, Pramata's team of experienced lawyers reviews each contract for key information and enters it into the platform.

Transform text into data

Data Organization & Structuring 

Contractual relationships are rarely defined in a single self-contained document. Your most important contracts reference additional documentation, such as attachments and exhibits. They are amended and change over time. They can even incorporate outside information such as pricing and regulations. To produce a single piece of data, you often must understand how multiple documents interact and which documents were in effect at a given time. Pramata untangles this information for you and enters data based upon your overall contractual relationships rather than single documents. We organize documents logically in easy-to-understand family trees. When your relationships change or are amended, we update the underlying data and provide insight into how things have changed over time.

Untangle complex relationships

Data Cleansing

Gaps in a company's documentation – missing amendments, missing pages, unexecuted contracts, or even missing contracts – represent potential risk in a company's relationships . One of the first challenges companies face when getting control of their contracts is centralizing documents in one place, identifying where these gaps exist, and closing them. This process requires significant manual effort and can take several weeks. Pramata recognizes this data cleansing exercise is critical to providing our customers intelligence that they can rely on for making decisions. Throughout our data extraction process, we bring key issues – such as missing amendments, illegible pages, and unexecuted contracts – to your attention for resolution.

Data Normalization

To effectively use contracts data, you must be able to find and analyze the information you need regardless of how it appears in your contracts. Because negotiations (and lawyers) create unique language, simply extracting information as it appears in documents is not enough to enable reliable reporting. Pramata enables reporting and analysis by extracting data based upon underlying meaning rather than text and entering it into the platform in a defined structure. This creates "buckets" of information that contain similar information, and makes it easy for our customers to ask important questions about their contracts, regardless of who drafted them or what language was used.

Normalize data to enable reporting

Data Quality Assurance

To deliver high caliber information to our customers, we built control mechanisms and quality thresholds throughout the extraction and normalization processes. The data we extract passes through four independent layers of quality assurance, with each layer designed to test specific characteristics of the intelligence. We not only confirm that data is accurate, we also confirm it is actionable and it makes sense from a business user's perspective. Additionally, internal teams dedicated to data quality and usability continue to conduct data audits, verify use cases, and ensure best practices on an ongoing basis even after the data is extracted.

      

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