As call centers grapple with the need to reduce costs while scaling up their operations, they are increasingly turning to automation solutions powered by artificial intelligence (AI). According to research firm TechSci Research, the global market for contact center AI could grow to nearly $3 billion in 2028, up from $2.4 billion in 2022. Additionally, a recent survey found that around half of contact centers plan to adopt some form of AI within the next year.
One company capitalizing on this trend is Retell AI, a startup that provides a platform for companies to create AI-powered “voice agents” capable of answering customer phone calls and performing basic tasks such as scheduling appointments. Retell’s agents are powered by a combination of large language models (LLMs) fine-tuned for customer service use cases and a speech model that gives voice to the text generated by the LLMs.
Retell’s co-founder, Evie Wang, highlighted the motivations driving the adoption of such solutions: “Companies with heavy call center operations, looking to scale quickly without the constraints of human contact center agents, are highly receptive to adopting effective AI voice agent solutions. This approach not only reduces their overall costs but also decreases wait times.”
Retell’s customers include contact center operators as well as small- and medium-sized businesses that regularly deal with high call volumes, such as the telehealth company Ro. These businesses can either build voice agents using Retell’s low-code tooling or upload a custom LLM (e.g., an open model like Meta’s Llama 3) to further tailor the experience.
Wang emphasized the importance of investing in the voice conversation experience, stating, “We don’t view AI voice agents as mere toys that one can create with a few lines of prompts, but rather as tools that can offer substantial value to businesses and replace complex workflows.”
In a brief test of Retell’s platform, the AI-powered voice agent demonstrated the ability to handle basic tasks like scheduling a hypothetical dentist’s appointment, asking relevant questions and responding promptly to answers and follow-up queries. While the synthetic voice quality may not be on par with industry leaders like Eleven Labs or OpenAI’s text-to-speech API, Wang acknowledged that the team has been focused on reducing latency and handling edge cases, such as interruptions that might occur in a conversation.
For basic tasks like appointment scheduling, automation through platforms like Retell appears to make sense, which is likely why both startups and big tech firms are offering competing solutions. However, the jury is still out on more complex queries, particularly given the tendency of LLMs to fabricate facts and go off track even with safeguards in place.
As Retell’s ambitions grow, navigating the well-established technical challenges in the space will be crucial. Wang remains confident in Retell’s approach, stating, “With the advent of LLMs and recent breakthroughs in speech synthesis, conversational AI is getting good enough to create really exciting use cases. We’re trying to make it easy for developers to build, test, deploy and monitor AI voice agents, ultimately to help them achieve production readiness.”
While the adoption of AI voice agents in call centers promises cost savings and scalability, the industry will need to address the inherent limitations and risks associated with these technologies as they become more widespread.
