SOLUTIONS
COMPANY
Neuphonic © 2026
How our voice AI is powering real products
CASE STUDIES
A WORLD LEADING OEM
The Challenge
Cloud TTS introduced latency, infrastructure dependency, and less control over the user experience. The OEM needed a model that could run efficiently within its own hardware and operating system environment, without relying on external cloud inference or dedicated accelerator hardware.
Our Solution
Neuphonic adapted its efficient TTS models to run in real time on-device, using CPU-only inference. The models were optimised for the OEM's hardware and software environment, proving that high-quality speech generation could happen locally, even within strict device-level performance constraints.
The Impact
Neuphonic's models achieved real-time on-device performance and improved latency and speed compared with the OEM's internal cloud-based benchmarks. This showed that responsive voice experiences could be delivered directly on device, reducing cloud dependency while improving user experience and deployment flexibility.
The Results
Real-time TTS running locally on device
CPU-only inference without dedicated acceleration
Improved latency versus internal cloud benchmarks
Faster speech generation in constrained environments
Reduced reliance on cloud infrastructure
Stronger path toward private, responsive, on-device voice AI
A leading OEM wanted to bring high-quality text-to-speech directly onto its own devices, running speech locally on CPU without relying on cloud inference.
By adapting Neuphonic’s efficient TTS models for custom hardware and operating systems, they achieved real-time on-device performance, faster speech generation, and lower latency than internal cloud-based benchmarks — creating a more private, responsive voice experience.
Real-time TTS on device
A world leading OEM × Neuphonic
Models
Solutions
Company
A WORLD LEADING OEM
The Challenge
Cloud TTS introduced latency, infrastructure dependency, and less control over the user experience. The OEM needed a model that could run efficiently within its own hardware and operating system environment, without relying on external cloud inference or dedicated accelerator hardware.
Our Solution
Neuphonic adapted its efficient TTS models to run in real time on-device, using CPU-only inference. The models were optimised for the OEM's hardware and software environment, proving that high-quality speech generation could happen locally, even within strict device-level performance constraints.
The Impact
Neuphonic's models achieved real-time on-device performance and improved latency and speed compared with the OEM's internal cloud-based benchmarks. This showed that responsive voice experiences could be delivered directly on device, reducing cloud dependency while improving user experience and deployment flexibility.
The Results
Real-time TTS running locally on device
CPU-only inference without dedicated acceleration
Improved latency versus internal cloud benchmarks
Faster speech generation in constrained environments
Reduced reliance on cloud infrastructure
Stronger path toward private, responsive, on-device voice AI
Real-time TTS on device
A world leading OEM × Neuphonic
A leading OEM wanted to bring high-quality text-to-speech directly onto its own devices, running speech locally on CPU without relying on cloud inference.
By adapting Neuphonic’s efficient TTS models for custom hardware and operating systems, they achieved real-time on-device performance, faster speech generation, and lower latency than internal cloud-based benchmarks — creating a more private, responsive voice experience.
A WORLD LEADING OEM
A leading OEM wanted to bring high-quality text-to-speech directly onto its own devices, running speech locally on CPU without relying on cloud inference.
By adapting Neuphonic’s efficient TTS models for custom hardware and operating systems, they achieved real-time on-device performance, faster speech generation, and lower latency than internal cloud-based benchmarks — creating a more private, responsive voice experience.
The Challenge
Cloud TTS introduced latency, infrastructure dependency, and less control over the user experience. The OEM needed a model that could run efficiently within its own hardware and operating system environment, without relying on external cloud inference or dedicated accelerator hardware.
Our Solution
Neuphonic adapted its efficient TTS models to run in real time on-device, using CPU-only inference. The models were optimised for the OEM's hardware and software environment, proving that high-quality speech generation could happen locally, even within strict device-level performance constraints.
The Impact
Neuphonic's models achieved real-time on-device performance and improved latency and speed compared with the OEM's internal cloud-based benchmarks. This showed that responsive voice experiences could be delivered directly on device, reducing cloud dependency while improving user experience and deployment flexibility.
The Results
Real-time TTS running locally on device
CPU-only inference without dedicated acceleration
Improved latency versus internal cloud benchmarks
Faster speech generation in constrained environments
Reduced reliance on cloud infrastructure
Stronger path toward private, responsive, on-device voice AI
Real-time TTS on device
A world leading OEM × Neuphonic
Your next breakthrough
is just a voice away.
Your next breakthrough is just a voice away.
Build it with Neuphonic.
SOLUTIONS
COMPANY
Neuphonic © 2026
How our voice AI is powering
real products
How our voice AI is powering
real products
CASE STUDIES
CASE STUDIES
SOLUTIONS
COMPANY
Neuphonic © 2026
Models
Solutions
Company