Gaining quick access to any legal contract or document quickly is key to any type of document management platform, much more so with time sensitive documents such as legal contracts. With A good document life cycle management system at the helm, most contracts should automatically be delivered under pre-determined conditions such as renewals. Experience shows that in many cases contracts frequently need to be accessed on occasions that weren’t foreseen when they were signed. The ability to quickly access any file within your firm’s repository for whatever reason, using whatever type of reasoning is essential for good contract administration.
This requirement demands powerful search capabilities that can cross reference different types of data in order to efficiently locate what you are looking for even when you don’t entirely know what it is that you are looking for. This type of task is the digital twin of locating a specific document you require, from some form of physical storage, say, a filing system. While in hardcopy searches having a top notch filing system is key, you still end up letting the fingers do the walking. Digital repositories require your fingers to do the searching.
In the simplest of digital searches you are most likely going to be able to search for a file name, and date. In such cases you better hope you remember the file name, or at least when it was created. Now let’s throw in a few curve balls. Let’s say that you are looking for a few contracts, or all the contracts that comply with industry or state regulations. Maybe you are looking for contracts that have lower or higher margins. You might be looking for all contracts that are about to expire in the next 6 months, or all the leases, or operations contracts, financial or employment contracts. CEO/CFOs look for contracts that carry liability or require investments, the list is too long. Another wild card in this scenario is the fact almost all contracts are saved as .pdf files which are essentially a non-textual and unsearchable image of the document. Let me show what kind of tools openSource offers its users in order to tackle these tasks. Our deep text search can be performed using three different datasets which when cross referenced can point you quickly in the right direction:
File Content
locate a file by searching for keywords and phrases that can be found anywhere within the textual content of the file. Most contracts are saved in the unsearchable Adobe .pdf file format. openSource automatically runs every contract loaded onto its servers through a powerful OCR (Optical Character Recognition) engine which creates a fully searchable html version of the file, and stores it alongside the original. The OCR engine is so rugged it can even handle hardcopy documents that where precariously positioned and scanned at an angle. This feature ensures that all text oriented files loaded onto the system can be searched by keywords and phrases.
Meta Data
In this reference, metadata is information used to describe digital data using a specific set of standards. A simplistic example of metadata would be tags that can be used to offer a descriptive clue as to the nature of the content in the file. Facebook allows users to tag themselves in photos thus enabling an aggregation of all the photos of that person. At openSource we call this type of descriptive data “term sheets”. Companies using openSource can customize metadata term sheets to fit their own organizational work process. By describing the contents and context of data files, one can learn for example, what type of contract this is, who authored it, under whose jurisdiction it falls, when it expires, is it regulated? Categorized? Active? etc. Many companies use simple spreadsheets to describe contract and document types. openSource enables an organization to customize and create as many can “term sheets” as required, in a way that will help employees locate files faster by referencing terms that are organic to the organizations work process. Under the openSource contract management, one can import all the fields used in the .XLS or .CSV file into a term sheet template, copy it, adjust it, and create other term sheets as needed.
File Name & date
locate a file by its name and/or date of execution. By cross referencing relevant keywords and terms with the appropriate descriptors in our metadata (term sheets) we are left with a short list of search results, which might still require some scrutiny. Poring over legal documents can be a taxing chore, and openSource offers tools designed to alleviate this burden. The first such tool Document Structure Analysis (DSA), presents the contents of each document viewed in an intuitive way within a hyperlinked environment that helps you quickly understand the relevance of your search results, and much more. Second come Match and Compare features that are designed to assist in locating similar content and differentiating between similarities. The features described next should not be seen as mere search tools, as they can be put to use in a host of different scenarios. Let’s take a quick look at these tools as they will both be covered extensively in the very near future:
DSA (Document Structure Analysis)
we take special pride in this feature, and believe it differentiates us from all of our competitors. DSA automatically parses every document loaded onto the platform, and returns a document, that describes the structure of the contract using a hyperlinked table of content. Demonstrating this feature requires a separate post (which will be published sometime soon), suffice it to say that searching for keywords within a multipage .pdf legal contract, will produce a table of content describing the structure of the contract with clear, color coded links to the location of the keywords within this structure. This feature requires no action on the users’ part, as the structure analysis is performed automatically, and presented by default whenever each document is viewed. The original un-parsed documents are kept alongside to view at will.
Document Compare & Match
Searching for a similar contract is often part of the authoring process. Contract templates are commonly used, but often need to be modified and adapted to a new set of terms, or a changing reality. Locating a similar contract to be used as a template often requires sifting through your contract repository for the right one. An initial content, or term sheet search might be required to zero in on the likely candidates. Once they are selected, the ‘match’ tool offers an intuitive interface that can quickly help you assess the relevance of each contract. Once a good candidate is selected, and modified to reflect the requirements of the new contract, the ‘compare’ tool comes into play. By microscopically comparing the new document with its original, this tool will find and display all changes made for inspection.
opensourceCM is a cloud-based SaaS (software-as-a-service) solution. When uploading a text or MS Excel document the application performs OCR, indexing and then recreates each document as an HTML document allowing easy document comparisons (e.g., between MS Word and scanned PDF docs). It also provides the ability to find words, values, phrases, terms of art or specific legal language within documents that are hyperlinked to the actual highlighted location in each document. This can be accomplished across document data sets that may comprise tens of thousands of documents.
Furthermore, opensourceCM provides a contract authoring workflow, calendar and notifications workflow, support SSO (single sign on) and encrypted secured access. The application offers the ability to simply create Negotiation Deal-Rooms and Users Data-Rooms (internal/External) or Flexible Bidding System with Advance Q&A. We offer an API (Application Processes Interface) Library with office365, BOX.COM, SalesForce, MS-Dynamics, NetSuite, OKTA, Dropbox, DocuSign to mention just a few.