Designing Hecttor: The UX Principles Behind Real-Time Voice AI

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Designing Hecttor: The UX Principles Behind Real-Time Voice AI

Anush Bichakhchyan

Anush Bichakhchyan

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When the user doesn’t see your product, every millisecond counts.

UX, user experience: why is the digital world so obsessed with this term? Back in the days when we used dial-up to access the internet, no one thought of experience. But the progress and technologies made us, users, pretty picky. And because everything is created for one purpose, to satisfy customers and gain trust, UX has become a doctrine. But what does UX mean in the contact center domain, and do technologies really care about the agent’s experience or is the customer the main character?

 

When you are in a line with an agent, you hardly imagine how they process data and how many interfaces they switch to get your issue resolved ASAP. On the other end of the line, we see agents who don't have time to think about tools. They're already thinking about the customer, the script, the call timer, and their KPIs. Adding another interface—another system to manage—isn’t a solution. It's a new source of stress. Yet this is how most voice AI technologies have approached "innovation": by layering dashboards, toggles, and analytics over conversations that are already cognitively demanding.

 

What gets overlooked is that voice is not just another data stream. It's the medium through which agents process, respond, and build rapport in real time. 

 

The UX of voice AI can't be designed like visual software. It must be designed like sound: invisible, intuitive, and immediate.

Why Voice UX is Fundamentally Different

Most UX design today is rooted in visual affordances. Users click, swipe, or tap to initiate and control an experience. In Voice AI and Hecttor AI, there's no such buffer. The user doesn’t click anything; they experience it. And that experience is driven by rhythm, clarity, and timing.

 

With visual elements, a broken component will make the user frustrated but it may not have a significant impact on the experience. In voice AI, if the AI system misfires—whether through latency, poor audio rendering, or robotic speech—the disruption is not minor. It breaks the conversation, increases misunderstanding, and may even escalate tension. In a domain where 90% of customers rate "immediate response" as critical to satisfaction, these tiny breaks in timing have compounding effects.

 

According to statistics, a delay of just 250 milliseconds in a customer interaction can degrade perceived empathy and attentiveness.

 

This is why real-time Voice AI can't tolerate the norms of other AI products. It can't afford buffering, retries, or batch processing. The interface is the conversation itself.

The Industry’s Missed Opportunity: Cognitive UX

Most voice AI solutions treat speech as a technical challenge—a problem of recognition, transcription, or translation. They build massive language models, then layer agent tools over them: dashboards, confidence scores, and real-time guidance panels. These systems are powerful. But they're cognitively expensive. 

 

One of the latest reports found that 67% of contact center agents using AI tools feel overwhelmed by having "too many systems" open during live calls.

 

The assumption is that more features equal more intelligence. But in reality, every added layer increases the cognitive load on the agent. In live calls, the brain can't switch contexts quickly. Asking an agent to read a dashboard while listening to emotional customer speech is a classic case of dual-task interference—a well-documented cognitive strain.

 

As described in “Cognitive Control in Media Multitaskers” research, multitasking in audio+visual contexts reduces task accuracy by half.

 

This isn’t just inefficient. It's unsustainable. And it leads to burnout, turnover, and poor CX outcomes. Most tools interrupt more than they assist.

 

They:

  • Overload agents with alerts and dashboards

  • Create latency in communication due to cloud processing

  • Apply robotic-sounding transformations that reduce speaker authenticity

  • Or require agents to use new interfaces

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Understanding Persona: Designing for the Agent

Having played for both teams, as call center agents and product designers, we recognized the problem of cognitive load and the struggle agents face. When building Hecttor, we used our experience and we started not with the AI but with the agent. We found the way to pack our technology that would bring significant change in agent experience in their minute-by-minute reality of handling 80+ calls per day.

 

Hecttor is not another control panel. It is a relief from misheard sentences and asking customers to repeat themselves to a clear, natural conversation and comprehension.

So we designed Hecttor to be cognitively weightless. No button. No dashboards. Just a voice AI that adapts and works in the background to improve comprehension by adjusting the speech to agent comprehension and enhancing the audio itself, not by simplifying it, but by making it more neurologically processable.

 

How?

  • We slow down only the parts of speech that matter—terms with high information density.

  • We preserve speaker identity, rhythm, and emotion.

  • We achieve sub-200ms processing latency to maintain natural dialogue flow.

  • We do it all locally, without GPU or cloud dependency.

No More Layers

We believe AI shouldn’t be a layer. It should be a channel. At Hecttor, the UX isn't about building a tool that agents use—it's about building a tool that helps them take full control of their productivity.

 

That's why we designed Hecttor to disappear. If agents notice it, we’ve failed. Success means nothing stands in their way. Not latency. Not dashboards. Not robotic filters.

Rethinking Voice AI Design

The challenge contact center agents are experiencing daily is not only the never-ending customer inquiries, but also interfaces that add to frustration. Businesses do business, true, but there should be something more behind the business: an excellent user experience without a learning curve, complicated navigation, and cognitive load. The industry needs to move away from designing for control and go towards designing for cognition. We don't need another "AI assistant" that interrupts or overexplains. We need systems that adapt to the rhythms of human thought and interaction.

 

In a world of eye-first interfaces, Hecttor is built for the ear. Not to be heard louder. But to be understood better.

 

 

Because real-time voice UX isn't about what you build. It's about what you remove.

 

What is voice UX and why does it matter in contact centers?

Voice UX (User Experience) refers to how users interact with voice-based technologies. In contact centers, voice UX is critical because agents rely on real-time audio to resolve customer issues. Poor voice UX can lead to misunderstandings, cognitive overload, and lower customer satisfaction.

How does traditional voice AI increase agent stress?

Traditional voice AI tools often add dashboards, alerts, and interfaces that distract agents during live calls. These systems demand multitasking, which increases cognitive load and leads to stress, slower response times, and burnout.

What makes Hecttor’s voice AI different from other solutions?

Hecttor is designed specifically for the agent experience. It operates in the background with sub-200ms latency, enhances audio clarity without robotic transformations, and requires no extra interfaces—reducing cognitive friction and improving call flow.

Why is cognitive load a problem in contact center technology?

Cognitive load refers to the mental effort required to process information. In contact centers, agents handle complex conversations while juggling multiple tools. High cognitive load leads to mistakes, fatigue, and poor customer experience. Reducing it is key to productivity and agent retention.

How does Hecttor improve voice UX for agents in real time?

Hecttor improves voice UX by slowing down only the most information-dense parts of speech, preserving emotion and clarity, and processing audio locally to avoid delays. This enables agents to better understand customers without extra mental strain or added software layers.