Real-time clinical dictation for the real world
Medical-grade speech recognition for real clinical workflows, not just demos...
The challenge
Edvak EHR is an AI-native EHR platform used directly in live clinical consultations. Clinicians dictate as they work, capturing notes and conversations in real time. Because speech is embedded directly within the EHR, transcription accuracy directly affects documentation integrity and automated workflows inside Edvak EHR.
Here’s what happens when it is not accurate. A doctor says “no fever and nausea” and the system transcribes “fever and nausea.” One dropped word, opposite clinical meaning.
As Edvak EHR evolved to support increasingly complex clinical workflows, the team needed speech recognition that could keep pace. The requirements were clear: faster streaming, better accuracy on medical terminology, and consistent reliability when conditions become chaotic.
They went looking for technology that would not buckle under real clinical pressure.
"Edvak’s AI-native EHR drives the next steps automatically inside the EHR, with clinicians able to review and adjust outputs in real time. That only works when speech understanding preserves critical clinical meaning in real conditions. Speechmatics ensures negations, medication names and subtle distinctions stay accurate, making downstream automation trustworthy at enterprise scale."
Vamsi Edara, Founder & CEO, Edvak EHR
Why clinical dictation breaks most ASR
Three factors make medical speech recognition uniquely difficult.
Challenge | Clinical reality | Impact |
|---|---|---|
Speed | Rapid dictation | Dropped negations |
Noise | Overlapping voices | Misrecognition |
Vocabulary | Drug names | Guessing errors |
1) Speed and small words Clinicians dictate quickly. Under pressure, ASR systems can drop short but critical words that determine meaning. “No pain” becomes “pain.” “Not responding” becomes “responding.” These errors directly impact documentation accuracy and downstream clinical workflows inside the EHR.
2) Noise and context scarcity Clinical environments are loud. Background chatter, equipment noise, overlapping voices. Short utterances lack context for the model to self-correct. Longer paragraphs provide breathing room. Rapid-fire phrases do not.
3) Vocabulary (Domain complexity) Medical vocabulary sits outside standard language models. Generic ASR systems lack the terminology and often guess incorrectly. Both brand and generic drug names are difficult to pronounce and rarely present in general training data.
All three challenges often occur simultaneously in everyday clinical use.
What Edvak needed
Speech recognition is embedded directly within Edvak EHR, powering real-time dictation and conversation capture inside live clinical workflows. When speech lags or fails, downstream EHR workflows stall. Performance is critical.
Two requirements were non-negotiable:
Invisible latency. Clinicians speak and text appears instantly. Even a few seconds of delay breaks clinical flow.
Unshakeable reliability. The system must keep pace with fast speech in noisy rooms. No stuttering. No gaps. No uncertainty about whether the system captured what was said.
Edvak EHR set a high bar: consistent low latency under real clinical pressure, accuracy on short critical phrases, and reliable handling of complex medical terminology. The goal was to support how clinicians naturally work, not force them to adapt to the technology.
Why Speechmatics
Edvak EHR required an ASR engine capable of operating as a reliable foundation inside an AI-native EHR platform, not merely as a dictation tool.
Rather than relying on benchmark scores alone, the team tested Speechmatics alongside alternative solutions under real-world clinical conditions. Performance under pressure mattered more than lab metrics.
Speechmatics stood out across multiple dimensions.
Capability | What it enabled in live workflows |
|---|---|
Consistently low latency | Fast, stable streaming in demanding clinical scenarios, allowing clinicians to dictate naturally without pauses or waiting. |
Strong medical language handling | Accurate recognition of specialized healthcare vocabulary, including clinical terminology, pharmaceuticals, institutional names, and brand-specific references. |
Robustness under pressure | Reliable performance despite fast speech, background noise, and interruptions, preserving critical small words such as “no” that determine clinical meaning. |
Context-aware self-correction | Real-time use of prior transcript output and spoken context to resolve ambiguity, improving accuracy on short phrases during live dictation. |
Custom vocabulary support | Domain biasing prioritizes predefined pharmaceutical and institutional terms when spoken audio closely matches, reducing errors on critical names. |
Built-in speaker diarization | Automatic identification of who said what within the same engine, simplifying conversation capture and eliminating the need for separate models inside the EHR. |
Across multiple evaluation rounds, Speechmatics delivered the performance Edvak EHR required.
The results
Edvak EHR achieved the performance targets it had set.
Medical terminology transcribes accurately. Fast speech preserves clinically critical words in short phrases. Pharmaceuticals and institutional names are captured correctly through custom vocabulary and domain biasing.
The instant feel clinicians expect is present, providing streaming transcription that keeps pace with real consultations.
Today, Speechmatics supports conversation capture and dictation across Edvak EHR deployments. Broad adoption reflects the reliability and real-time consistency required by the platform.
Accurate transcription also strengthens everything that follows. Within Edvak EHR, clinical decision support, code detection, structured documentation, and workflow automation all depend on a reliable speech foundation. When that foundation is solid, the systems built on top function reliably and safely.
What's next?
Within Edvak EHR, the speech transcript has become the primary input for documentation, coding signals, and workflow automation.
Using a single engine across dictation and conversation capture simplifies feature development and enables new capabilities inside the EHR.
Edvak EHR plans to layer additional workflow automation directly on top of real-time speech within the system. With reliable speech recognition in place, automated actions triggered by clinician voice input become safer and more scalable.
The takeaway
For Edvak EHR, real-time clinical dictation requires more than accuracy. It demands low and consistent latency, robustness to noise and fast speech, and reliable handling of complex medical language.
Speechmatics delivers on these requirements, enabling smoother clinician workflows today and supporting the continued evolution of intelligent automation inside an AI-native EHR platform.
