4 NLP Innovators You Should Know About

The past decade has seen natural language processing (NLP) applications evolve from mere novelties of limited usefulness to highly advanced use cases like automating customer service and legal document review. Thanks to NLP, we can now control digital systems with natural-language queries, either spoken or written, instead of relying solely on simple commands like numerical values, clicks, and keywords.

Today, 42% of internet search queries are voice-powered, but that’s far from the only use case for NLP. Almost half of U.S. households now own smart speakers, and chatbots have already become the norm in customer service. Thanks to recent advancements in the technology, NLP now has even more use cases, ranging from epidemiological investigation to transcribing legal case files into actionable data.

Among the endless possibilities, here’s how some of the top innovators in the NLP space are leveraging this powerful new technology:

1. True Lark: Automating Digital Marketing Communications

True Lark is an NLP-powered communications platform that automates customer support and appointment-booking for brick-and-mortar businesses. Far more than just another chatbot, it can respond seamlessly to everyday language, along with its many quirks, misspellings, and slang. Embodied by its highly customizable AI, dubbed ‘Sasha’, True Lark is made to be used in place of front desks, call centers, and answering services to provide 24/7 availability and a distraction-free personalized customer experience.

Sasha was made possible by annotating customer conversations at massive scale. Thanks to a partnership with CloudFactory, True Lark was able to achieve a much faster time to market. This approach has helped them develop a truly cutting-edge system for customer support, proactive marketing, and customer sentiment analysis. For their clients, this means having an easy and dependable way to automate many routine customer communications and marketing processes, thereby freeing up time to focus on the things that still require a human touch.

2. Textio: Empowering Organizations to Write Better Job Postings

Textio describes itself as an augmented writing platform centered around helping businesses write more compelling job postings. It relies upon advanced insights into the way people use language to help HR teams create a culture of inclusion and belonging through their writing. It takes style and grammar checkers to a whole new level by suggesting alternatives that help reduce bias and provide insight into company culture.

Textio is built on the back of natural language processing and understanding (NLP/NLU). By leveraging insights from recorded conversations and millions of data points collected from real-world recruitment outcomes, it even understands the subtle differences in the way people of different genders and age groups interpret certain words and phrases. In other words, it is like having a professional editor, proofreader, and sensitivity reader together in the form of an AI-powered application. Moreover, it uses NLP-driven insights to allow recruiters to tailor their messaging based on their own company culture, job types, and even locations.

3. Heretik: Transforming Legal Contracts into Actionable Data

Reviewing and exploring legal documents has never been a quick and easy process, and that is something Heretik is determined to change. Their solution uses NLP to translate contracts and other legal documents into actionable insights that drive smarter decision-making in less time. It simplifies eDiscovery by automating the review of documents, allowing businesses to instantly learn things like which contracts are coming up for renewal, which ones require extra regulatory responses, and which ones contain errors and inconsistencies.

Legal contracts might tend to follow certain standards to avoid misinterpretation, but that does not mean complex corporate agreements always follow a consistent and structured format—at least not as far as a computer is concerned. There are many nuances from one agreement to the next, and for Heretik to offer value across the many areas of law, it needed to draw upon huge amounts of training data. Working with CloudFactory helped them label these massive data sets at scale so the platform could better interpret a wide range of contract types from lease agreements to employment contracts to major corporate transactions.

Hear from Heretik themselves in this video.

4. Linguamatics: Fighting COVID-19 with Insight Generation

Linguamatics has taken a particularly novel approach to NLP by using it to translate biomedical texts into structured data for the betterment of public health. Among their recent innovations is the COVID-19 Evidence Hub, which gathers unstructured data from many different sources—including scientific literature, clinical trial records, medical records, social media, and news reports. By bringing such a vast trove of information together, the solution captures key insights that help deepen their understanding of how the pandemic is developing, as well as the best measures for fighting it.

As a text-mining platform, Linguamatics examines huge collections of documents to capture key facts and information. In addition to other methodologies, it uses NLP to extract insights from across a range of domain-specific areas. It also focuses on the integration of customer and patient vocabularies to better understand the real meaning of their contents, instead of relying solely on simple keyword-based analyses.

How Can a Managed Workforce Help You Develop Your NLP Model?

NLP is all about capturing the numerous subtleties and irregularities of language, whether it’s spoken or written. Whether you’re training a chatbot to deliver better customer service, building a customer sentiment analysis tool, or a legal contract review tool, partnering with a managed workforce lets you scale the data-labeling demands of NLP model development without losing control or compromising on quality.

Our natural language processing services help you scale text and audio annotation by teaming up with a managed workforce with the ability to understand and interpret complex and nuanced language.

Building a better chatbot with text annotation services

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