Kira systems: The emergence of contract automation and technology
Using technology to draft, store, review, and analyze contracts has been in a constant state of development and improvement for a couple of decades, and the pace has significantly quickened in the last 5-7 years.
Tools for drafting contracts have come a long way since lawyers finally set aside their quill pens and inkwells. For a long time the typewriter was the predominant technology. The first real digital technology breakthroughs were the introduction of personal computers and the development of the WordStar word processing program in the 1970s. With word processors, contract drafters were able to do more than just draft contract terms; the software automated things like the numbering of sections and insertion of cross references to those sections.
By the 90s, “document assembly” systems such as HotDocs and Contract Express further facilitated contract generation. These tools use guided forms and questionnaires to gather data on requirements and then generate contracts. More tools, such as Deal Proof (now part of Thomson Reuters), and Eagle Eye (now part of Litera), further facilitated the drafting process by automating the cross-checking of defined terms and section references. These were rule-based systems and were probably among the first widespread applications of early Artificial Intelligence to contract drafting. As with most of the contract technology to that point, the focus was on the front-end process of contract drafting rather than extraction of value and insight in the post-drafting stages of contract lifecycle management.
Finalized executed contracts were mostly still stored in paper, tucked into filing cabinets or archived away in a basement file room. They were not, for the most part, accessible digitally except perhaps in scanned formats that were not easily searchable. Contracts were not typically seen as collections of data; each contract was independent as a document and there were limited opportunities to extract insights from larger sets of contracts.
Yet there was clearly enormous value in those previously executed agreements. Tools for searching contracts existed by this point; in the 90s law firms and corporate legal departments had begun implementing document management systems, such as OpenText and iManage, that housed these contracts in their original digital formats. But these systems were primarily for version control and record keeping purposes. Searching was based on keywords. Contracts often use unpredictable and inconsistent language to express the same concepts. So even though DMS and other search engines now enabled lawyers to search through large bodies of contracts, finding clauses and terms that matched keyword searches would inherently be hit-or-miss.
The value locked in those signed contracts is enormous. Within a business, events will arise during which knowing what is in one’s contracts becomes mission-critical. Regulatory changes such as GDPR or accounting standards are two examples. And there is perhaps no moment more critical than a merger or acquisition. Much of the value of any company is represented in its contracts: customers’ payment obligations, the consistency and stability of its suppliers, limits on liability, the relationships with employees and contractors. Mergers and acquisitions lawyers have the unenviable task of needing to quickly review and verify that all the legal agreements are in place, in order to confirm that the company being acquired is worth what the amount to be paid for it.
That M&A due diligence process was almost completely manual, and consisted of young associates reviewing boxes full of printed contracts, often piled high in physical deal rooms. In the mid-90s, the internet enabled the birth of “virtual data rooms” like Intralinks and Merrill, which allowed scanned copies of these files to be shared securely online. Nonetheless most of the actual contract review work remained fully manual, with young lawyers given the task of reading through hundreds or thousands of contracts hunting for specific terms and clauses to identify risks. It was repetitive and boring for the lawyers, and extremely expensive for the client.
Reporting on the findings was also frustratingly manual and incomplete. In many cases the volume of documents was too large to review everything, and the parties would agree that the risk assessment would be made only on contracts over some dollar threshold or that met some subjective guesses as to materiality. This inevitably led to some risks being missed or underestimated. Compiling the results of such a limited review was still a herculean task. For weeks, bleary-eyed associates would pore though page by page, retyping their findings into Microsoft Word charts and tables that would allow them to start to form a risk assessment.
This all culminated in a “diligence memo” which spelled out a set of findings and recommendations to the acquirer in narrative form. While spreadsheets were available around the same time as word processing tools, and might have provided a better tool for data manipulation, lawyers tended to stick with the technology they had already begun to adopt: word processing programs and their tables function. This technology didn’t really automate anything about the process, but it provided the ability to organize, sort, and manipulate data that was extracted and collected manually.
It soon became clear, however, that technology could be used to capture the output of that review—to turn the unstructured text in contracts into rows and columns of data.
By the time a critical mass of lawyers were up and running with some basic productivity tools including word processing and search, the legal industry had some of the building blocks for a more accurate and efficient way to create, store, and analyze contracts. Contract data was digitized and there were better tools for search and analysis. But the entire contract lifecycle was still mostly manual and relied heavily on human creation and analysis.
The next leaps forward in contract analysis had yet to come. That will be the subject of Part II of this series.