Built for
AI Voice Therapy Platform
A voice therapist that remembers you, answers in under 100ms, and never closes.
Real-time spoken conversation, dual-memory recall that spans months, and emotion-aware responses in both English and French. Private, judgment-free, and available at any hour of the day.
Sub-100ms voice
- English and French - Memory across sessions - 3x user retention growth
The problem
Support that too many people can't reach
Reaching a therapist often means clearing hurdles first: the cost of a session, a schedule that never lines up, or a commute you cannot make. For many people, opening up to a stranger feels intimidating, and worry about who hears it keeps them silent.
Listen answers with a private voice therapist available 24/7. People speak freely, without appointments or judgment, and get supportive, emotionally aware responses in a space they control.
One conversation, held in memory
A single session view shows the live voice exchange, the emotional read of the moment, and the past context Listen carries forward.
What we built
A voice therapist built to listen, remember, and respond in real time
Listen holds a spoken conversation the way a person would. It hears you, picks up on how you feel, recalls what you shared before, and replies fast enough that the exchange feels like talking, not waiting. It works in English and French, and stays available whenever someone needs it. Every session is private, and each one builds on the last.
Real-Time Voice
Talks back in under 100ms, in two languages
Full-duplex streaming (Real-Time Duplex Audio Engine) keeps voice moving both ways at once, so replies land in under 100ms. The voice switches instantly between English and French (Multilingual Voice Adaptation), matching whichever language the user speaks.
Memory & Emotion
Remembers the conversation, and how it felt
Two memory layers (Dual Memory System) recall the thread of a conversation and retrieve related context by meaning, while sentiment detection (Emotion-Aware Context Processing) weights what matters emotionally in each moment.
Solutions We Provided
Cut duplex audio latency to under 100ms.
For natural back-and-forth conversation.Weighted emotional signals.
So responses match the user's state.Combined two memory systems.
To recall context across sessions.
Switched voices between English and French.
On the fly, mid-conversation.
Thinking about a voice-first product of your own?
We build real-time, memory-aware AI systems from concept through deployment.
Our process
How we built Listen
Conceptualization
Design
Development
Deployment
What’s inside
Under the hood
The hard part of voice therapy is timing and memory. Listen streams audio in both directions at once and adjusts its buffers on the fly, holding responses under 100ms even when the network wavers, while two memory systems run side by side: one keeps the thread of the conversation, the other searches past sessions by meaning and emotional weight. That combination is what lets it recall a worry from last week or update a fact after a user's life changes.
Placeholder · architecture diagram: duplex audio path, dual-memory retrieval, and event-driven session sync.
The Results
From 600ms to under 100ms
Before
Slower, laggier sessions.
Duplex audio lagged at 600ms, and each session took 5 seconds to load. Long enough to break the conversation's rhythm before it began.
After
Real-time, remembered.
Responses now land under 100ms, sessions load in 1.5 seconds, emotional context is recalled with 92% accuracy, and users return three times as often.
Audio latency
600ms to under 100ms
Emotional recall
Accuracy in emotional-context recall
Session load
5 seconds to 1.5 seconds
User retention
In user return rates
Frequently asked
Yes. It recalls context across sessions, from a worry mentioned last week to a fact that changes after a user moves, and tracks it accurately over spans up to six months.
Have a voice or memory-aware product in mind?
We design and ship real-time AI systems, from the first concept through deployment. Tell us what you are building and we will map the fastest path to a working product.
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