The system can extract concepts, instead of just keywords, for example descriptions of dates (“not later than ten business days after demand therefore”) or amounts (“equal to three percent (3%) of the shareholders' equity of XY corporation”)
The system can interpret provisions and classify clauses, even when the formulation differs. For example, the solution uses inferences to classify a provision as either (1) standard, (2) negotiated or (3) needs review
The solution is able to parse and extract information from tables regardless of the row/column format in the PDF document
SMEs define extraction targets and inferences, upload documents and start the training system to automatically perform extractions without the need or cost of an AI expert
The system can be trained by Subject-Matter Experts (SMEs) starting with as few as 50 documents. Once the SMEs have defined custom extraction targets and annotated a few documents, they can train the system to automatically perform the extractions. SMEs also have the ability to review results and can continue to fine tune the system as part of a continuous learning process.
Who uses Cortical.io Contract Intelligence?
- Banks and financial institutions
- Consulting companies
- Companies that have to manage large repositories of legal documents
How a Big Four accounting firm reduced processing time of lease agreements by 80%view case study
Contract Intelligence FAQs
- What kind of information can the engine extract from documents?
- Can the engine extract data from tables that are in PDF files?
- How does the engine integrate into my existing contract management system?