Relevant clinical and pharmaceutical information is typically free-form, poorly organized and spread across disparate data sources, from siloed EHRs to difficult-to-edit PDFs. Another important pain point that NLP can help solve is navigating the vast troves of unstructured data in healthcare. Contact centers are an unglamorous back-office function that happen to also be a staggeringly massive market—an estimated $340 billion in 2020, on its way to $500 billion by 2027. But thanks to the remarkable advances underway in language AI, reliable and high-quality machine translation is fast becoming a reality. This novel paradigm for AI-augmented writing is already starting to become a reality, driven forward by a handful of interesting startups. Most often, foundation models are built and open-sourced by the publicly traded technology giants—e.g., BERT from Google, RoBERTa from Facebook.
Given language’s foundational importance throughout society and the economy, few areas of technology will have a more far-reaching impact in the years ahead. While some clinicians and patients are uneasy about the idea of a machine providing mental health support, the fact is that we face a critical shortage of trained therapists and affordable mental healthcare today. The average wait time to see a mental health professional in the United States is nearly 2 months; last year, almost 60% of those with mental health issues did not receive any treatment. Given this reality, these AI-powered conversational agents may have an important role to play providing patients with support in an accessible, scalable way.
“Multimodal AI” like this—that is, AI that ingests and synthesizes data from multiple informational modalities at once, like image and audio—will play a central role in AI’s future. But thanks to recent breakthroughs in AI, opportunities now exist for startups to build search tools for data modalities beyond text—and no new modality represents a bigger opportunity than video. One final enterprise search startup worth keeping an eye on is Hebbia, which is building an AI research platform to enable companies to extract insights from their private unstructured data. The first category of language AI startups worth discussing is those players that develop and make available core general-purpose NLP technology for other organizations to apply across industries and use cases.
Gong’s closest competitor Chorus.ai exited to ZoomInfo last year in a $575 million sale, further solidifying Gong’s status as the category leader. More profoundly, the inability for people around the world to understand one another inhibits the advancement of grand global goals and species-level harmony. But in a polyglot world like ours , language barriers have always been an unavoidable reality. Given the caliber of the company’s founders and backers, expect Inflection AI to make waves in the world of language AI before long. Given Microsoft’s massive investments in and deep alliance with the organization, OpenAI can almost be considered an arm of the tech giant.
Rasa’s AI stack is open-sourced, with over 600 contributors and over 10 million downloads. This open-source strategy gives Rasa’s customers greater transparency and control over the conversational AI interfaces that they build and deploy. Leveraging the latest transformer-based techniques, ZIR is seeking to develop search technology with true semantic comprehension (as opposed to keyword-based matching) and more sophisticated multilingual capabilities.
Its AI platform takes a video with spoken dialogue in one language and applies AI to quickly reproduce that video with the dialogue in another language, doing so in a way that the speakers’ lip movements continue to look natural. Think of it as sophisticated dubbing, except that it can be carried out automatically and at scale. Invoca is an AI-powered call tracking and conversational analytics company that brings the depth of marketing analytics traditionally limited to digital consumer interactions. The company specializes in the fields of inbound call marketing, call tracking, call intelligence, and pay-per-call advertising. And make no mistake—given the scale of the challenge, the market opportunity here is massive. Facebook alone reportedly spent $13 billion on content moderation between 2016 and 2021, including paying Accenture $500 million per year to work on the problem.
AI-based translation tools have historically been deeply flawed (as anyone who remembers using AltaVista’s Babel Fish service in their younger days can attest). To temper expectations, we should not expect that today’s NLP will immediately take over all writing from humans. Some forms of writing—brief formulaic content like marketing copy or social media posts—will yield more naturally to these new AI tools than will others. Original, analytical, creative work—say, op-eds, thought pieces or investigative journalism—will resist automation for the time being.
Assembly is an AI company building a platform of APIs to transcribe and understand audio data. Its platform automatically converts audio or video files and live audio streams to text. Users can do more with audio intelligence like summarization, content moderation, topic detection, and more.
While opportunities for vertical-specific NLP applications do exist in some other industries, for instance financial services and law, no sector offers a greater breadth of language AI use cases than healthcare. Algolia is a more well-established player in enterprise search; the company has raised over $300 million in venture funding since graduating from Y Combinator in 2014. Algolia offers an API that enables its customers—from tech companies like Slack to media businesses like the Financial Times—to embed search experiences in their websites and applications.
Starting from boosting customer satisfaction, identifying new drugs to improving the quality of research datasets, Artificial Intelligence has changed every aspect of the tech and non-tech industries. Mobvoi, also known as Chumenwenwen, operates as an artificial intelligence company that develops technologies in Chinese language speech recognition, natural language processing, and vertical mobile search. It offers a Chinese SmartWatch Operating System that features mobile intelligence voice search for iOS, Android, Android Wear, Google Glass, and WeChat. In a different corner of the healthcare universe, Infinitus is another fast-growing startup to keep an eye on. Infinitus offers voice AI technology—what the company has termed “VoiceRPA”—to automate routine phone calls for providers, insurers and pharmacies. Infinitus’ product is directly comparable to players like Replicant and AI Rudder, discussed above in the “Conversational Voice Assistants” section, except that it is built specifically for healthcare.
The most well-funded of these competitors is Ada Support, a Toronto-based startup that has raised close to $200 million from blue-chip venture capitalists. Ada powers automated interactions for enterprises in customer support and sales across text-based channels including web chat, SMS, and social media, intelligently looping in a human agent when needed. With a long list of marquee clients including Zoom, Shopify, Verizon and Facebook, Ada powers over one billion customer interactions annually. Over the years, AI has grown and has overtaken almost every global industry.
A related application is chatbots for mental health, a use case that has seen tremendous growth during the pandemic. These “AI therapists” are freely available and immediately responsive via mobile app for individuals to discuss their lives and problems with. They do not represent a full clinical solution but rather one potentially useful tool for those in need.
AI-driven audio cloning startup gives voice to Einstein chatbot https://t.co/5SdjexRrRj
— ModernFrock (@ModernFrock) April 17, 2021
DigitalOwl is an Israeli startup applying machine learning to enable health insurers to automate the review of medical records, allowing these insurers to process claims more efficiently and accurately. DigitalOwl claims that its technology can analyze and summarize a typical medical case in 3-5 minutes, audio startup gives voice to chatbot compared to 3-4 hours for a human reviewer, while identifying twice as many medically relevant datapoints. Like Duplex, Replicant’s voice AI is designed to sound as natural as a human (the company’s name is a tribute to the bioengineered robots from Blade Runner that are indistinguishable from humans).
Cresta focuses on providing personalized coaching to contact center agents in real-time, as opposed to post-conversation, with an omnichannel platform that spans phone calls and text chats. One last startup of note in this category is Resemble AI, which specializes in generating realistic human voices using generative adversarial networks . Resemble’s synthetic voices can speak with all the nuance and range of a human—for instance, whispering or communicating with various emotions—and are finding use cases from video games to advertising. The company recently made headlines when its technology was used to reproduce Andy Warhol’s voice for an upcoming Netflix documentary. A promising group of startups has emerged to provide the technology and infrastructure for companies across industries to create and operationalize chatbots.
Any platform that features user-generated content of any kind—from gaming companies to dating apps—is susceptible to the proliferation of toxic language. At scale, it becomes impossible for companies to rely on humans alone to monitor and moderate all this content. Replicant is one promising startup applying voice AI to automate contact center agent activity, reducing wait times for customers and cutting costs for companies. Replicant spun out of Atomic, the high-profile startup studio that has produced companies like Hims and OpenStore. One exciting startup building next-generation video search capabilities is Twelve Labs, which announced its seed financing earlier this month. Twelve Labs fuses cutting-edge NLP and computer vision to enable precise semantic search within videos.
AI-driven audio cloning startup gives voice to Einstein chatbot https://t.co/3b5CWujrij
— The Blogger (@TheBlogger_in) April 19, 2021
Replicant’s technology is equipped to handle a wide range of call center use cases, from billing to customer surveys to subscription renewals. When its AI encounters a complex conversation topic that it cannot resolve on its own, it pulls in a human agent. These AI-powered conversational interfaces are commonly known as chatbots—though some startups today prefer to avoid that terminology and its mixed connotations, given a premature hype cycle for chatbot technology about five years ago. The runaway leader in this category is Gong, which has raised close to $600 million in venture funding.
Language is a slippery, nuanced phenomenon; it is impossible to build an AI model today that can reliably detect every instance of fake news or sexual harassment. But an intriguing group of startups is applying NLP to help organizations make a dent in the problem. The problem of toxic content has been a reputational nightmare and a technological quandary for social media platforms like Facebook in recent years. As the previous section highlighted, contact centers are a massive—and massively underdigitized—market. There is tremendous opportunity to transform the world of contact centers with software and machine learning. Gong is an impressive business, with incredible revenue growth and a long list of blue-chip customers.
Constructor.io is another fast-growing competitor in this space that focuses specifically on ecommerce search and discovery. Dialogflow is a conversational user experience platform enabling brand-unique, natural language interactions for devices, applications, and services. Notable is an AI-powered health start-up that automates and digitizes every audio startup gives voice to chatbot physician-patient interaction. It automates the recording of doctor’s visits and updating of electronic health records. The company has developed a technology that uses natural language processing and voice recognition to automatically record doctor-patient interactions and structure the data for inclusion in a patient’s medical records.
MetaDialog has been a tremendous help to our team, It’s saving our customers 3600 hours per month with instant answers. AI Engine connects to your website and any other content you have, and automatically reads everything, and within an hour it is ready to answer the questions. AI Engine does not get tired or sick, it is always there to answer your customers’ questions, no matter what the situation is. MetaDialog`s AI Engine transforms large amounts of textual data into a knowledge base, and handles any conversation better than a human could do. Ultimately, by deciphering the “language” of nucleic acids, genes, amino acids and cells, today’s language AI will give us a deeper understanding of how life itself works. In terms of venture capital funding, there is perhaps no hotter category in NLP today.