ElevenLabs debuts Conversational AI 2 0 voice assistants that understand when to pause, speak, and take turns talking

Over years of operations, some mature industries have collected enormous amounts of data. Telecom is one of the key industries that has accumulated zillions of data that allows it to train voice AI systems (such as chatbots, for example) and solve user problems without involving a person. In addition to these core features, ElevenLabs’ new platform supports multimodality, meaning agents can communicate via voice, text, or a combination of both. This flexibility reduces the engineering burden on developers, as agents only need to be defined once to operate across different communication channels. This update introduces a host of new features designed to create more natural, intelligent, and secure interactions, making it well-suited for enterprise-level applications. The Los Angeles-based company has more than 50 million global users thanks mainly to its conversational AI technology.

Enterprise-grade standards and pricing plans

By leveraging advanced algorithms and user data, agents can deliver highly targeted product recommendations tailored to individual preferences and behaviors. AI models can anticipate user needs and preferences with remarkable accuracy by analyzing buyer signatures across the open web, resulting in increased conversion rates. AI agents’ ability to continuously learn and adapt based on user interactions can ensure that recommendations remain relevant and impactful over time, driving long-term customer loyalty and retention.

• Then and there, high-level specialists can help clients in difficult cases while the most common and nonhuman issues of clients can be outsourced to AI voice systems.
• By enhancing articulation, filling in pauses or smoothing out disfluencies, AI acts like a co-pilot in conversation, helping users maintain control while improving intelligibility.
• By the end, you won’t just have a functional AI agent—you’ll gain a deeper understanding of the principles that make conversational systems reliable, scalable, and engaging.
• In banking, AI could flag fraudulent attempts to mimic a customer’s voice for transactions by analyzing inconsistencies in vocal inflection or biometrics.
• Most providers offer free trials, so you can try out different services before committing to a paid plan.

T-Mobile was able to automate this simple task by rolling out a chatbot that helped customers make payment arrangements. What T-Mobile didn’t expect is to get such a high return on investment (ROI) launching a small side project, which turned into a widely used tool. If we want the future of conversation to be truly intelligent, it must also be inclusive. Enterprises adopting AI-powered interfaces must consider not only usability, but inclusion. According to the World Health Organization, more than 1 billion people live with some form of disability. Accessible AI benefits everyone, from aging populations to multilingual users to those temporarily impaired.

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This modular design allows developers to easily add new tools as requirements evolve.

The AI insights you need to lead

• Strategically speaking, organizations must incorporate good governance when automating a conversational AI lifecycle.
• If we want the future of conversation to be truly intelligent, it must also be inclusive.
• Raghu Ravinutala is CEO and cofounder of enterprise-grade conversational AI platform Yellow.ai.
• It can now analyze sentiment, infer context and offer proactive solutions—creating dynamic, human-like interactions.

It aims to perfectly combine natural language processing (NLP) with traditional software or an interactive voice recognition system so that customers could get support through either a spoken or typed interface. By developing a strong strategy, enterprises can use generative AI to elevate customer experiences by providing personalized, natural-language interactions with customers. They should look for potential use cases within their organization that it can solve now and continue to follow this trend.

With smartphones becoming an integral part of our daily lives and users accustomed to voice-enabled interactions, businesses are looking at voice AI use cases that stretch beyond customer service and sales growth. Speech recognition is quickly gaining prominence in the realms of banking, insurance, travel, automobiles and healthcare. HR, marketing, entertainment and even everyday functions like public transportation are realizing the technology’s potential to accomplish more by simplifying archaic processes and increasing overall efficiency.

And, it is seeing good demand, with one source projecting that the market will grow 20% year on year to $32 billion by 2030. Using advanced tools to monitor metrics like engagement, response times and satisfaction scores can help uncover insights for strategy enhancement. Praveen Gujar has 15+ years’ experience launching enterprise products in digital advertising and AI/ML. Boris Kontsevoi is a technology executive, President and CEO of Intetics Inc., a global software engineering and data processing company. Many retailers were talking about record downloads, and those with no pre-built apps were eager to catch up quickly.

As generative models continue to evolve, it will become even better at understanding the nuances of human conversation and providing more relevant and useful responses. Our north star is to serve human kind with technology innovation, so that all can access information and services in their own languages. This is being achieved by providing conversational AI agents to businesses, which enables businesses to automate customer conversations and drive revenue growth, cost savings, and customer satisfaction. From understanding user intent to generating coherent responses, conversational AI platforms help business create lifelike conversations that meet customer needs efficiently.

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Organizations can initiate multiple outbound calls simultaneously using Conversational AI agents, an approach well-suited for surveys, alerts, and personalized messages. According to Jozef Marko from ElevenLabs’ engineering team, Conversational AI 2.0 is substantially better than its predecessor, setting a new standard for voice-driven experiences. The launch comes just four months after the debut of the original platform, reflecting ElevenLabs’ commitment to rapid development, and a day after rival voice AI startup Hume launched its own new, turn-based voice AI model, EVI 3. MeetKai has rolled out new creator tools as part of its goal to create a portfolio of metaverse and conversational AI technologies.