DICR: AI Assisted, Adaptive Platform for Contract Review


  • Dan G. Tecuci EY AI Lab (Ernst & Young)
  • Ravi Palla EY AI Lab (Ernst & Young)
  • Hamid R. Motahari Nezhad EY AI Lab (Ernst & Young)
  • Nishchal Ahuja EY AI Lab (Ernst & Young)
  • Alex Monteiro EY AI Lab (Ernst & Young)
  • Tigran Ishkhanov EY AI Lab (Ernst & Young)
  • Nigel Duffy EY AI Lab (Ernst & Young)




In the regular course of business, companies spend a lot of effort reading and interpreting documents, a highly manual process that involves tedious tasks, such as identifying dates and names or locating the presence or absence of certain clauses in a contract. Dealing with natural language is complex and further complicated by the fact that these documents come in various formats (scanned image, digital formats) and have different degrees of internal structure (spreadsheets, invoices, text documents). We present DICR, an end-to-end, modular, and trainable system that automates the mundane aspects of document review and allows humans to perform the validation. The system is able to speed up this work while increasing quality of information extracted, consistency, throughput, and decreasing time to decision. Extracted data can be fed into other downstream applications (from dashboards to Q&A and to report generation).




How to Cite

Tecuci, D. G., Palla, R., Motahari Nezhad, H. R., Ahuja, N., Monteiro, A., Ishkhanov, T., & Duffy, N. (2020). DICR: AI Assisted, Adaptive Platform for Contract Review. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13638-13639. https://doi.org/10.1609/aaai.v34i09.7106