Home
Latest reporting
News
At its NYC Summit, ElevenLabs introduced tools for fine-tuning AI models, domain-specific solutions, and its new Interaction Engine for conversational AI.
At its New York Summit on November 11, 2026, ElevenLabs unveiled a series of advancements aimed at redefining how businesses interact with customers and employees through artificial intelligence. The company introduced new models, tools, and deployment options designed to make AI interactions more natural, intuitive, and tailored to specific industries and businesses.
Advances in AI Models and Customization
ElevenLabs announced updates to its conversational AI models, emphasizing their ability to adapt to specific industries and use cases. CEO Mati Staniszewski highlighted the importance of domain-specific solutions, stating, “Our mission at ElevenLabs is to solve human-technology interaction, and for the first time, it’s solvable.”
The company showcased its domain-specific Speech-to-Text models, such as Scribe v3 Medical, which is optimized for healthcare terminology. This model can accurately distinguish between complex terms like “cycloserine” and “cyclosporine,” reducing errors in critical contexts. ElevenLabs also revealed plans to develop a financial services model and announced that businesses will soon be able to fine-tune open-source language models and ElevenLabs’ voice models using their own data. This customization will allow companies to optimize for specific metrics, such as customer satisfaction scores, and create reinforcement-learning stacks tailored to their unique needs.
Introducing the Interaction Engine
One of the key announcements was the preview of the Interaction Engine, a system designed to orchestrate conversations by managing turn-taking, interruptions, and the selection of appropriate language models. The engine can assign simpler tasks to cost-effective models while reserving more complex interactions for advanced frontier models. This approach aims to optimize performance and reduce operational costs.
Enhancements to ElevenAgents
ElevenLabs also introduced significant upgrades to its ElevenAgents platform, which is used to deploy and manage voice and chat agents across various business functions. A new Memory feature enables agents to retain and act on information shared by customers in previous interactions. For example, an agent can remember a customer’s language preference or specific constraints, such as availability after 5 PM, and use this information to personalize future interactions. This capability allows agents to build a cumulative understanding of each customer, enhancing the overall experience.
Additionally, the platform now supports Routines, which automate follow-up tasks after customer interactions. This feature is designed to streamline workflows and reduce the manual effort required to complete post-conversation activities.
Strategic Vision for AI Interaction
Staniszewski emphasized the growing importance of conversational AI, predicting that it will become as essential to enterprises as cloud computing or payment systems. “Every business will need to reinvent how it interacts with its customers, employees, and the wider world,” he said. By offering tools for customization, domain-specific optimization, and seamless interaction management, ElevenLabs aims to position itself as a leader in the AI interaction space.
