May 25, 2022 | Read time 3 min

Kao Data to Host Speechmatics’ HPC and AI Supercomputer, Expanding Deep Learning Capabilities

Speechmatics’ new high-performance computing (HPC) deployment includes NVIDIA A100 GPUs, housed within an advanced Supermicro computing infrastructure, which will be hosted at Kao Data’s Harlow campus.
Kao Data to Host Speechmatics’ HPC and AI Supercomputer, Expanding Deep Learning Capabilities
Speechmatics
SpeechmaticsEditorial team

Kao Data, the specialist developer and operator of high-performance data centres for enterprise, cloud, HPC and AI, has today announced it has secured a new customer contract with Speechmatics, the leading speech recognition technology scaleup, providing highly accurate speech-to-text to global enterprise businesses.

Speechmatics’ new high-performance computing (HPC) deployment includes NVIDIA A100 GPUs, housed within an advanced Supermicro computing infrastructure, which will be hosted at Kao Data’s Harlow campus. The supercomputer will allow Speechmatics to expand its GPU-accelerated neural network research and development, supporting increasing customer demand for its leading speech recognition technology.

Kao Data was chosen as the UK’s premier location for HPC and AI, in addition to its commitments to sustainability and energy efficiency. Speechmatics’ high-density supercomputer will benefit from bespoke colocation, an SLA-backed PUE of 1.2, and will be powered by 100 percent renewable energy.

Recognised in both 2020 and 2021 by the FT1000 as one Europe’s fastest-growing companies, and named within NVIDIA’s prestigious Inception Program, Speechmatics exploits deep learning technology to deliver highly accurate and ultra-fast speech-to-text technology. The company utilises NVIDIA’s acclaimed GPU hardware to complete its aim of understanding every voice, regardless of demographic, accent, or dialect.

Speechmatics’ supercomputer will work in tandem with its hyperscale cloud deployments, providing a pioneering example of fluent, hybrid HPC in-action. Central to this capability is Megaport’s hyperscale connectivity solutions at Kao Data’s Harlow campus, which provides seamless connectivity and on-ramps between the on-premises supercomputer, and Speechmatics’ instances within Amazon Web Services (AWS), Microsoft Azure, and Google Cloud.

“Powering modern Machine Learning research and development requires an advanced computing infrastructure which only becomes more demanding the more you grow and scale.” Said Will Willams, VP Machine Learning, Speechmatics. “As we continue to develop our technological edge through the use of self-supervised learning in our models, it’s crucial to ensure our data centre provider can scale with our compute demands but in a sustainable way. Kao Data was the obvious choice for us as the best HPC provider in the UK with the benefit of being run off renewable energy.”

“The opportunity to support Speechmatics in this crucial phase of the company’s expansion is an exciting prospect for our organisation, and further underpins Kao Data’s position as the UK’s preeminent provider of sustainable data centres for HPC and AI,” said Lee Myall, CEO, Kao Data. “We look forward to working closely with Speechmatics to help power and support their unique approach of applying neural networks to speech recognition.”

Speechmatics’ founder, Dr Tony Robinson, pioneered the approach of applying neural networks to speech recognition back in the 1980s, and when higher performance CPUs appeared in the early 2000’s, the company was among the first developers to utilise the technology to process large datasets at volume. Today, NVIDIA GPUs have further accelerated Speechmatics’ speech-to-text capabilities, and its ability to support leading organisations such as Deloitte, Veritone and Red Bee Media. The company’s flexible API easily integrates into customers services, solutions, and applications to offer the most accurate AI-powered transcription capability, with 33 languages already available.

For more information visit Kaodata.com

Latest Articles

Carousel slide image
Use Cases

The court reporter shortage crisis: data, causes, and what legal teams are doing about it

The court reporter shortage is reshaping litigation. Explore data, causes, and how legal teams are using digital reporting and AI transcription to adapt.

Tom Young
Tom YoungDigital Specialist
Carousel slide image
Use Cases

What Word Error Rate Is Acceptable for Legal Transcription?

Word error rate for legal transcription has no single acceptable threshold. But knowing how accuracy, audio quality, and review obligations connect to real legal risk is what separates a reliable transcript from a costly one.

Tom Young
Tom YoungDigital Specialist
[alt: Bilingual medical model featuring terms related to various health conditions and medications in Arabic and English. Key terms include "Chronic kidney disease," "Heart attack," "Diabetes," and "Insulin," among others, displayed in an organized layout.]
Product

Speechmatics achieves a world first in bilingual Voice AI with new Arabic–English model

Sets a new accuracy bar for real-world code-switching: 35% fewer errors than the closest competitor.

Speechmatics
SpeechmaticsEditorial Team
[alt: Illuminated ancient mud-brick structures stand against a dusk sky, showcasing architectural details and textures. Palm trees are in the foreground, adding to the setting's ambiance. Visually captures a historic site in twilight.]
Product

Your voice agent speaks perfect Arabic. That's the problem.

Most voice AI models are trained on formal Arabic, but real conversations across the Middle East mix dialects and English in ways those systems aren’t built to handle.

Yahia Abaza
Yahia AbazaSenior Product Manger
new blog image header
Technical

How Nvidia Dominates the HuggingFace Leaderboards in This Key Metric

A technical deep-dive into Token Duration Transducers (TDT) — the frame-skipping architecture behind Nvidia's Parakeet models. Covers inference mechanics, training with forward-backward algorithm, and how TDT achieves up to 2.82x faster decoding than standard RNN-T.

Oliver Parish
Oliver Parish Machine Learning Engineer
[alt: Healthcare professionals in scrubs and lab coats walk briskly down a hospital corridor. A nurse uses a tablet while others carry patient charts and attend to a gurney. The setting conveys a busy, clinical environment focused on patient care.]
Use Cases

Why AI-native EHR platforms will treat speech as core infrastructure in 2026

As clinical workflows become automated and AI-driven, real-time speech is shifting from a transcription feature to the foundational intelligence layer inside modern EHR systems.

Vamsi Edara
Vamsi EdaraFounder and CEO, Edvak EHR