The category of Contract Lifecycle Management (CLM) software has been rapidly evolving from its document management and audit roots to automation of complex legal language and sophisticated measurement of exposure to risk. That came out loud and clear when I interviewed Bill Hewitt, CEO of Exari last year for my book, Silicon Collar
Our vision is a world where the contract process is virtual. Companies negotiate with each other in cyberspace, taking best practices from a universal library of clauses and precedents or recommendations from a contract ‘machine.’ Automatic scoring of risk gives the negotiator visibility into how exposed they are, allowing them to ensure they are putting proper protections in place. Finally, the contract is analyzed against similar previous contracts and the libraries are updated even as the contract whizzes through cyberspace with electronic counterparty signatures. The contract and its core data are stored, and now are ready to inform downstream and upstream systems of the new rights and obligations.
He told me this week about his acquisition of a UK contract data discovery and analytics vendor, Adsensa. It broadens out Exari functionality, and also extends their vertical reach of his customer base in Insurance, Financial Services and Professional Services, to name their top three. With over 250 customers worldwide including 9 of the top 10 insurance companies and the worlds largest professional services firm, Exari now has a broad set of use cases around new, legacy and third-party contracts that most other vendors will take a while to catch up with.
As many vendors, especially new entrants with Big Data/AI pedigree position their tools to mine contract data, I asked Bill if he is concerned about that competition. His response “Other solutions either take a discovery approach, a document approach or a process approach only. By providing all three, we give every business user access to their critical contract data in support of their contracting process and decision making around risk.”
