What does Speechmatics do?

Speechmatics provides speech technology and Voice AI for enterprises, offering accurate Speech-to-Text, Text-to-Speech, and Voice Agent solutions. Our models understand every voice and accent across 55+ languages, helping businesses unlock the full potential of voice data.

How accurate is Speechmatics Speech-to-Text?

Speechmatics delivers best-in-market accuracy, achieving up to 99% word accuracy and 96% medical keyword recall in industry benchmarks. Our models handle multiple accents, noisy environments, and multi speakers with ease.

What makes Speechmatics Text-to-Speech different?

Our low-latency Text-to-Speech (TTS) delivers lifelike, human-sounding voices with sub-150ms latency that is ideal for real-time conversations. Developers can stream natural speech in multiple voices and deploy it in the cloud, hybrid, or on-prem for privacy and control.

Can I build real-time voice agents with Speechmatics?

Our voice AI enables developers to build real-time voice agents that listen, understand, and respond naturally. Plug in fast with a flexible API and native integrations to power your AI voice agents.

Which industries use Speechmatics?

Speechmatics is trusted by organizations in media, healthcare, contact center, finance, education, and accessibility. Our technology powers transcription, translation, call analytics, and voice AI applications worldwide.

Speech-to-Text optimized for laptop

Enterprise-grade Speech-to-Text running locally on Mac and Windows devices. Sub-second latency, no infrastructure costs and audio that never leaves the machine. Full speaker diarization and identification included.

✅ Runs on Laptop Hardware

✅ 55+ Languages

✅ CoreML & DirectML Optimised

[alt: Laptop with speech-to-text feature showing speaker labels and audio waveforms on a dark screen with green accents.]

Trusted by millions of users globally

Case study

Prosodica | Case study

Driving better conversations at scale

Leveraging speech recognition to track customer interactions, highlight key insights, and raise contact center performance

Case study

AI Media | Case study

Delivering 120X more with voice AI

Powering live content through AI-powered transcription, built on industry-leading voice AI

Case study

Prosodica | Case study

Driving better conversations at scale

Leveraging speech recognition to track customer interactions, highlight key insights, and raise contact center performance

Case study

AI Media | Case study

Delivering 120X more with voice AI

Powering live content through AI-powered transcription, built on industry-leading voice AI

Why run offline STT on the laptop?

Reliable transcription regardless of network conditions, with data that stays private and features that match the cloud.

Shift Compute to the Edge

Offload transcription from cloud to the device
Predictable licensing model
Scale without scaling your server fleet

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No Network Required

Works when Wi-Fi drops
Critical for clinical and legal environments
Sub-second latency, no network dependency

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Audio Stays On-Device

GDPR, HIPAA, and air-gapped ready
Compliance by architecture
Sell into regulated & government accounts

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Cloud-Grade Features

Strongest on-device STT model available
Full speaker diarization and ID
55+ languages, real-time and batch

Shift Compute to the Edge

Offload transcription from cloud to the device
Predictable licensing model
Scale without scaling your server fleet

No Network Required

Works when Wi-Fi drops
Critical for clinical and legal environments
Sub-second latency, no network dependency

Audio Stays On-Device

GDPR, HIPAA, and air-gapped ready
Compliance by architecture
Sell into regulated & government accounts

Cloud-Grade Features

Strongest on-device STT model available
Full speaker diarization and ID
55+ languages, real-time and batch

Engineered for Laptop Silicon

Built for the hardware your users already have.

Runs on Mac

Optimized for CoreML

OSmacOS v14 Sonoma+

HardwareApple M1 or newer

RecommendedmacOS v26 Tahoe

AccelerationNeural Engine + GPU

Runs on Windows

DirectML optimized · GPU compute

OSWindows 11

HardwareIntel / AMD / ARM

Recommended2GB VRAM min

AccelerationDirectML GPU compute

Built for where your users already work

Laptop-first workflows

When your users need transcription that works everywhere their laptop goes. On a plane, in a courtroom, at the bedside.

Excels in scenarios requiring privacy, offline capability, or handling sensitive data in regulated environments.

Video Editing & Captioning

Local video editing tools with real-time transcription baked in. No uploads, no waiting, no cloud dependency.

Healthcare & Legal Scribes

Ambient scribe and dictation tools that keep working when hospital Wi-Fi drops. Patient and client data never leaves the device.

Regulated Industries

Financial services, insurance, and legal. Sectors where compliance by architecture beats compliance by policy.

Government & Law Enforcement

Transcription where on-device processing simplifies security clearance and removes cross-border data transfer concerns.

Edge AI Assistants

Deploy to devices, assistants, and enterprise systems without server costs or bottlenecks. Real-time, always available.

Note-Taking & Meetings

Meeting transcription that works in air-gapped environments, on flights, and in sensitive boardrooms.

Not all on-device STT is created equal

Here's what sets Speechmatics apart from open-source alternatives shipping stripped-down server models.

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Accuracy

Cloud-Parity Accuracy

Our 2026 on-device model delivers the same accuracy as our cloud STT. Same architecture, distilled and quantized for laptop silicon with hardware-native acceleration.

[alt:A digital transcript interface showing a dialogue between three speakers discussing a weather forecast, with text bubbles clearly separated by speaker labels.]

Features

Full Speaker Diarization & Identification

Includes our speaker diarization and speaker identification, making it the strongest speech-to-text model available for local execution.

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Scale

Millions of Professionals. Billions of Words.

Powering ISVs in video editing, legal, healthcare, and media production. Not a lab demo. Production workloads, shipping today.

[alt:A laptop device displaying an audio waveform visualization on its screen, with a location pin icon floating above to symbolize local processing or location services.]

Future

Built for the On-Device Era

Local AI isn't a fallback. It's the architecture. Edge-first compute is here. Speechmatics On-Device is a first-class deployment target, not a stopgap until connectivity returns.

The Speechmatics Difference

Speechmatics delivers the best accuracy, features, and enterprise reliability your business demands.

2026 Quality Step Change Substantial improvements make this equal to our cloud solution. Same architecture, optimized for local hardware with CoreML and DirectML acceleration.
Battle-Tested at Scale Proven in production with millions of professionals using our on-device speech-to-text across video editing, legal, healthcare, and media workflows.
Enterprise Support & SLAs Dedicated engineering support, not community forums. Enterprise-grade SLAs for mission-critical deployments.

Deploy enterprise STT on every laptop

Join leading ISVs building privacy-first, laptop-native applications with Speechmatics On-Device.

Offline speech-to-text FAQs

How much does it cost?

Pricing is based on your deployment volume and use case. Speak to our sales team for a tailored quote and volume-based discounts.

What hardware and devices do you support?

Operating System	Hardware requirements
MacOS v14 Sonoma or later, Tahoe v26 recommended	M1 or newer
Windows 11	Intel/AMD/ARM (with GPU 2GB)
Other Hardware	Get in touch if you have different requirements

How does on-device accuracy compare to cloud?

Our 2026 on-device model has parity with the Speechmatics Standard cloud model. Same underlying architecture, distilled and quantized for local hardware. Includes full speaker diarization and speaker identification, making it the strongest speech-to-text model available for local execution.

What about CoreML and DirectML optimization?

The on-device model is compiled with hardware-native acceleration paths. On Mac, it leverages CoreML to run on the Neural Engine and GPU. On Windows, it uses DirectML for GPU compute. This means maximum throughput within a minimal resource envelope. No platform-specific code from your side.

What are the resource requirements?

Requires approximately 1 CPU core, an AI accelerator (Neural Engine on Mac, GPU on Windows), and ~800MB of system memory. No external GPU or dedicated inference hardware needed. Standard business and consumer laptops handle it comfortably. Contact us to learn more about specific deployment configurations.