A Wave Of Billion-Dollar Language AI Startups Is Coming
Yet as anyone who has experienced writer’s block can attest, writing can be a frustrating experience. The act of translating inchoate thoughts into well-crafted language—of finding the right words—can be time-consuming and unsystematic. In today’s information-based economy, perhaps no skill matters more than effective writing.
AI-driven audio cloning startup gives voice to Einstein chatbot – Yahoo Singapore News
AI-driven audio cloning startup gives voice to Einstein chatbot.
Posted: Fri, 16 Apr 2021 07:00:00 GMT [source]
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. 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). Replicant’s technology is equipped to handle a wide range of call center use cases, from billing to customer surveys to subscription renewals.
“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. A nascent ecosystem of startups is at the vanguard of this technology revolution. These companies have begun to apply cutting-edge NLP across sectors with a wide range of different product visions and business models. 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. AI Rudder sells to customers in financial services and e-commerce, two industries that make extensive use of call centers.
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. Based in the U.K., Logically focuses on misinformation and disinformation. (The latter is the subset of the former that is spread to deceive intentionally.) Its platform relies on a large team of expert human reviewers working in tandem with its AI system. Many of Logically’s clients are governments, which use its technology for issues including national security, election integrity and COVID-19 misinformation.
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. Yet certain repeatable principles and tactics do exist that, if systematized, can meaningfully improve a sales team’s performance. The interesting question—for Lilt and for the entire industry—is whether and how quickly the humans in the loop can be phased out in the years ahead.
The pandemic has driven rapid growth for AI Rudder, whose revenue quadrupled last year. The company’s AI system can not only speak a wide range of different languages but can also aidriven audio startup voice to chatbot adopt the appropriate regional accent depending on the caller. The leading player in this category is Moveworks, which raised a $200 million Series C from Tiger Global last year.
Integrate with APIs and Tools
Given the size of the market, plenty of smaller startups have emerged with similar AI-driven product offerings. Notwithstanding earlier false starts, chatbots today have begun to gain real market adoption, thanks to improvements in the underlying NLP as well as in companies’ understanding of how to best productize and deploy these bots. Challenging Google directly will, to state the obvious, be an uphill battle. There is also significant opportunity for startups in search beyond the consumer internet search market with which Google has become synonymous. AI Engine automatically processes your content into conversational knowledge, it reads everything and understands it on a human level. From misinformation to cyberbullying to hate speech to scams, harmful online content is a massive and growing problem in today’s digital world.
- There is tremendous opportunity to transform the world of contact centers with software and machine learning.
- The interesting question—for Lilt and for the entire industry—is whether and how quickly the humans in the loop can be phased out in the years ahead.
- 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.
- Twelve Labs fuses cutting-edge NLP and computer vision to enable precise semantic search within videos.
- There is no one particular NLP “killer app” in healthcare; rather, startups have identified a wide range of different use cases to which language AI can be valuably applied.
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. Textio, LitLingo, and Writer are three newer entrants using next-generation language AI to build advanced Grammarly-like solutions for more targeted use cases. Textio focuses on hiring and recruiting, LitLingo on business compliance and risk management, and Writer on company-wide style and brand consistency. Search has been dominated by a single player for so long that it is often seen as an unpromising or even irrelevant category for startups. But there is also tremendous opportunity in this category for younger startups.
Full-fledged Conversational Interface Platform
The company’s target customers include health insurers, pharmaceutical companies and medical device companies. All four of the companies mentioned so far use AI primarily to provide recommendations and insights on existing text that humans have already written. The next frontier in AI-augmented writing will be for the AI to generate novel written content itself based on guidance from the human user. Building a state-of-the-art NLP model today is incredibly resource-intensive and technically challenging. As a result, very few companies or researchers actually build their own NLP models from scratch.
Constructor.io is another fast-growing competitor in this space that focuses specifically on ecommerce search and discovery. Following in Duplex’s footsteps, a handful of startups have developed voice AI technology that can engage in nuanced automated phone conversations. While Google’s Duplex is a consumer-facing tool , these startups’ go-to-market efforts focus on the enterprise. And no enterprise opportunity looms larger for this technology than contact centers.