Precise, Unambiguous Meaning Is Critical. With Vital Text Systems, It’s Possible!
Throughout all phases of product development, requirements documents are used to detail operational necessities, implementation strategies, risks, operating instructions, regulatory and industrial standards, and other considerable parameters. These, and other like texts, are referred to as “high-value” documents.
In the United States alone, organizations produce an average of 1.4 billion high-value documents each year, at an average cost of roughly $2,000 per document. That’s a 2.8-trillion-dollar investment.
Research has shown that, whether authoring or reviewing a document, unaided humans tend to miss many problematic structures in text. Humans also fail to perceive how many important words, terms, and phrases can be misconstrued by readers with different frames of reference.
As a result, every day, companies sign off on expensive documents fraught with weak or ambiguous language which jeopardizes assets, the organization itself and, in worst case scenarios, even human lives.
At Vital Text Systems, we believe a $2,000 document should not put lives or revenue at risk. Especially now that we provide a solution for only pennies per page.
The CSRT (a collaboration of the FAA & Boeing) concluded that ambiguities in these documents were the underlying cause of many problems, like the lithium-ion battery production issues. Issues that caused the FAA to ground the entire 787 fleet for over 90 days, resulting is hundreds of millions of dollars in lost revenues for Boeing and its airline partners. Read the FAA report here.
The Thoratec HeartMate II pocket system controller, for an implanted heart pump, was recalled by the FDA. But the recall was not because of a manufacturing defect.
Seemingly small language flaws and ambiguities in the labeling, and written installation procedure, led to misunderstandings which resulted in several injuries and 4 fatalities. Read the FDA report here.
High-value documents are found in nearly every business today, from small tech start-ups to Fortune 500 companies. These documents touch nearly every aspect of product development and are often considered the "knowledge real estate" of the organization.
If your organization writes or reviews requirements documents, proposals, instructions, standards, or briefs, then Vital Text Systems Analytic Service helps you ensure those documents contain ironclad, linguistically hardened, unambiguous language - helping your organization avoid potentially dire consequences.
Other commercially available requirements engineering tools address requirements quality with project management features. Vital Text Systems is the only tool, available, that addresses the issues of language fidelity at the document authoring and/or review levels.
Grammar checkers are great! Don't get us wrong. We think they're great tools to help you write better. But, as the name implies, they are all about grammar (and syntax).
No grammar issue ever caused a $100 million misunderstanding and no one ever died from bad grammar (though some may have wished they had).
Vital Text Systems is the only technology which helps comprehensively reduce defects caused by imprecise, vague, ambiguous, or incoherent language- and our patent (USPTO #9,678,949) proves it!
We're also the only solution that provides real-time feedback to document authors and reviewers- helping increase their knowledge of terms and language usage, which helps reduce at-risk language in their future work.
By fixing errors at their root, Vital Text Systems saves time, money, and even lives.
Vital Text Systems (VTS), providesa patented analytic software tool, Vital Text Systems Analytics (VTAS). VTAS enhances the comprehensibility and reliability of language in written texts of requirements documents (e.g. technical specifications, training manuals, and instructions). More specifically, VTAS is a language analysis software system that flags “at-risk” or weak language in highly important documents.
VTAS implements multiple layers of analysis combining computational linguistics technology (i.e. natural language processing), machine learning (i.e. predictive analytics) using progressive learning with real human assessment of language, and scientific cognitive science evidence to support the discovery and identification of weaknesses in natural language.
Our patented technology is, in essence, an analysis engine analyzing the linguistic structures in large documents, incorporating numerous classes of risky language patterns (e.g. misuse of pronouns, confusing syntactic structures).
We analyze your written text and provide a report covering four areas of at-risk language:
In addition to language analysis, VTS also provides an interactive framework that connects our patented system with the document author.
The system reports to the author four crucial pieces of information:
See for yourself! Try our patented language analysis tools for yourself with our risk-free trial.
We provide several methods of experiencing the Vital Text Analytic Service (VTAS):
With 30 years experience managing software teams, Gordon is an expert in agile, and plan-driven, systems engineering. He has also trained many teams on effective requirements engineering techniques.
Wayne is the chair of the linguistics department at University of Southern Maine. He specializes in the psychological aspects of language and is the author of the English4Engineers curriculum.
Chris has 20+ years experience in web development, eCommerce, business solutions, and public speaking. Past clients include BarnesAndNoble.com, FedEx, Citi Group, and KPMG. He believes AI should help people do their jobs, not replace them.
Matthew has 5 years experience in web and desktop software development. He specializes in Microsoft .Net but is always willing to branch out to try new technologies and strives to understand the bigger picture of how systems interact.
Eric has 20 years of experience in eCommerce, online learning, multimedia, and systems administration. He enjoys working closely with researchers and has a passion for machine learning applications and improving engineering teams through continuous delivery practices.
Tony has a PhD in natural language processing from the University of Groningen and a master's degree in linguistics from Trinity College, Dublin. He has published research in the fields of computational syntax, named entity recognition, and sentiment analysis.
Jackson is a student of linguistics and computer science, with a particular interest in semantics and in algorithms.