March 31, 2016 | Resources
Over the past decade, the demand for eDiscovery software has grown dramatically, and there is now a multi-billion dollar market for it.
September 14, 2014 | Resources
Software can’t accurately identify non-standard contract clauses unless it’s highly accurate at identifying contract clauses in the first place.
July 30, 2014 | Resources
Spotting outlying contract provisions isn’t as much fun as finding the 16 differences between these two images. Fortunately, simple software can help on the contract side.
July 16, 2014 | Resources
If you only need contract provision extraction software to review agreements you specifically trained it for (which are in the form of clean scans), rules- and comparison-based tech should work fine.
June 1, 2014 | Resources
In the previous post in the Contract Review Software Buyer’s Guide, we explored the human element of building contract provision extraction software.
May 5, 2014 | Resources
Good way to build accurate contract provision extraction models? tl;dr: If you wouldn’t trust the people who instructed a contract review system to accurately review contracts, can you trust results from the system they built?
March 19, 2014 | Kira Technology
ML-based contract provision models can be robust enough to work on poor quality scans and unfamiliar agreements, includes video showing this.
January 31, 2014 | Kira Technology
Put contract provision examples in, get provision models out. If machine learning is so powerful, why would anyone build a contract provision extraction system any other way?
December 13, 2013 | Resources
The past several posts in the Contract Review Software Buyer’s Guide have gone into details of how manual rule and comparison powered systems actually find contract provisions, and included a case study on a well-funded vendor’s experience with manual rules.
November 1, 2013 | Resources
The two previous installments of the Contract Review Software Buyer’s Guide covered how manual-rule based contract provision extraction systems—while relatively easy to set up and add provisions to—underperform on agreements and provisions that are not identical or very similar to ones they were built to review (”unfamiliar documents”).