Teneo, a a provider of agentic artificial intelligence technology, today introduced a real-time >voice AI development and testing platform that addresses unpredictable user expectations, optimizing cognitive load, and natural conversation.
"Every conversational designer knows the pain of spending months perfecting dialogue flows, only to watch them crumble when exposed to real user behavior," said Per Ottosson, CEO of Teneo, in a statement. "Users don't speak perfect sentences. They interrupt, rephrase, use incomplete thoughts, and bring contextual assumptions that many design tools simply can't anticipate. Our platform gives designers the ability to hear and optimize how people actually talk, in real time."
Teneo's real-time voice AI testing platform tackles the following three core pain points of conversational design:
- Pain Point #1: Unpredictable User Expectations: Traditional conversational design relies on training data based on "proper" speech patterns, but real users speak with incomplete sentences, omit subjects, rephrase mid-conversation, and assume contextual information. Teneo's native testing capabilities enable designers to hear actual speech patterns immediately, allowing them to optimize how people really communicate rather than how they theoretically should communicate.
- Pain Point #2: Cognitive Load Management: Unlike text interfaces that users can review and navigate, voice interactions must be processed sequentially in real time, creating significant cognitive burden. Designers struggle to balance information density with comprehension, often discovering their carefully structured responses overwhelm users in practice. Teneo AI allows designers to test and refine information architecture while hearing the actual cognitive impact on users.
- Pain Point #3: Natural Conversation Flow: Creating natural-sounding conversations requires precise control of pauses, emphasis, volume, and rhythm, elements that are impossible to evaluate without hearing the actual output. Traditional design tools provide no way to test human-like speech patterns until full deployment, leading to robotic, unnatural interactions that damage user experience.