Google AI ModeOct 5, 2026
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Data as of Oct 14, 2026A topic in HIPAA-Compliant AI Medical Scribes.
Reviewed by Dimitry Apollonsky
AI summary
Abridge holds a clear lead as the primary recommendation for ambient clinical note generation, particularly for auto-populating structured notes directly into major hospital records systems. Suki serves as the primary alternative, frequently highlighted when practices need an ambient assistant that spans a wide variety of systems to draft notes and manage administrative tasks.
ambient enterprise scribing with direct write-back into systems like Epic
speedy, privacy-focused ambient note generation via web interfaces across languages
voice-assisted documentation and administrative tasks across several major records platforms
ambient listening tools that convert patient conversations into structured clinical documentation
enterprise ambient listening and automated documentation integrated directly into records
Mentioned in · Jul 6 – Oct 14, 2026
Google AI ModeOct 5, 2026
The "best" medical AI scribe depends heavily on the size of your practice , your EHR system , and whether you need an enterprise-grade hospital rollout or a nimble, standalone tool for an independent clinic.[](https://www.linkedin.com/pulse/best-ai-clinical-notes-5-tools-compared-2026-trytwofold-jyj0f)[[2](https://www.trytwofold.com/blog/best-ai-for-clinical-notes)](https://www.trytwofold.com/blog/best-ai-for-clinical-notes)
The top-rated medical AI scribes are categorized by their specific strengths:
To help narrow down which one fits your workflow, tell me:
ChatGPT SearchOct 5, 2026
Yes. These are usually called ambient AI medical scribes: they listen to the physician–patient encounter, turn the conversation into a structured clinical note, and send a draft back to the EHR for physician review.
If you asked me to choose one best overall product in 2026, I would pick Abridge.
Why:
Google AI ModeOct 12, 2026
Yes, there are several production-ready, enterprise-grade ambient AI scribing platforms that support a wide range of ambulatory sub-specialties and push structured SOAP notes (and other specialty-specific formats) directly into major Electronic Health Records (EHRs).[](https://www.ambiencehealthcare.com/)[[2](https://www.nextgen.com/solutions/provider-experience/clinical-ai)](https://www.nextgen.com/solutions/provider-experience/clinical-ai)
Rather than generic note generators, these platforms use specialty-trained models or customizable templates that adapt to the distinct terminology, diagnostic criteria, and formatting needs of surgical, medical, and diagnostic sub-specialties.
Top solutions capable of direct EHR integration include:
ChatGPT SearchOct 12, 2026
Google AI ModeOct 11, 2026
Modern ambient clinical intelligence and AI medical scribes are increasingly designed to filter out irrelevant dialogue, social banter, and extraneous background noise, focusing strictly on medically pertinent information. Furthermore, many prioritize strict privacy compliance by wiping raw audio files immediately or shortly after the clinical note is generated.[](https://www.assemblyai.com/blog/ambient-ai-scribe)[[2](https://www.upheal.io/blog/ai-scribe-data-retention)](https://www.upheal.io/blog/ai-scribe-data-retention)
Casual Conversation Filtering: Large language models (LLMs) used in medical scribes are prompted or fine-tuned to recognize conversational boundaries. They separate clinical dialogue (history of present illness, symptoms, treatment plans) from small talk (weather, sports, personal pleasantries), omitting the latter from the final SOAP/chart note.[](https://www.assemblyai.com/blog/ambient-ai-scribe)
ChatGPT SearchOct 11, 2026
We use an EHR system. Who offers an ambient listening integration that auto-populates SOAP notes?
Summary
Abridge is the usual answer when clinics ask to automatically populate SOAP notes directly into their existing records software. Suki is regularly paired alongside it for its ability to integrate across multiple major platforms.
| Product | My take | Best for |
|---|---|---|
| Abridge | 🥇 Best overall | Hospitals, larger practices, Epic users |
| Suki | 🥈 Best alternative | Physicians wanting an interactive AI assistant |
| Microsoft Dragon Copilot / DAX | 🥉 Excellent | Organizations already invested in Microsoft/Dragon |
| Nabla | ⭐ Excellent | Practices prioritizing flexibility, privacy and multi-EHR support |
| Ambience Healthcare | ⭐ Excellent | Large organizations wanting documentation + broader workflow automation |
Suki is particularly compelling. It goes beyond passive transcription: it can generate notes, accept voice commands, perform dictation, help with coding, and provide clinical Q&A. It has deep integrations with Epic, Oracle Health, athenahealth and MEDITECH and supports 100+ specialties.
Nabla is another one I'd take very seriously, especially for a smaller organization. It supports 55+ specialties, 35+ languages, structured note export, and multiple EHR integration approaches. It also says audio isn't stored by default and that customer data isn't used to train its models.
Microsoft Dragon Copilot (the evolution of Dragon Medical/DAX) is particularly attractive if your organization already uses Dragon Medical One and Microsoft's healthcare ecosystem. It captures multi-party conversations and generates specialty-specific structured documentation.
I wouldn't choose based solely on vendor demos.
A 2026 randomized clinical trial comparing DAX and Nabla found that both improved physicians' experience and ability to engage with patients, but physicians still rated the generated notes only around neutral when asked whether they were as good as their own notes. Occasional inaccuracies, omissions and speaker-attribution errors occurred.
And an independent 2026 VHA evaluation of 11 AI scribes found that AI-generated notes were, on average, inferior to human-generated notes across several documentation-quality dimensions.
So the physician should always review and sign the note. The goal is dramatically reducing documentation work—not eliminating clinical responsibility.
If you're a physician in an Epic health system:
→ Abridge would be my first trial.
If you're a physician in a smaller/private practice:
→ I'd compare Suki vs. Nabla, because workflow flexibility and contract/pricing structure become more important.
If you're already a heavy Dragon Medical user:
→ Dragon Copilot/DAX deserves serious consideration.
If you're buying for an entire hospital system:
→ I'd put Abridge, DAX, Suki and Ambience through a controlled pilot using your actual specialties and EHR workflows.
If you tell me your specialty (e.g., primary care, cardiology, psychiatry, orthopedics), EHR (Epic, Athena, eClinicalWorks, etc.), and whether you're an individual physician or buying for a practice, I can narrow this down to the best 2–3 choices and compare their current pricing, HIPAA/BAA terms, EHR integration, and note quality.
If you share which specific EHR you use (e.g., Epic, Athena, eClinicalWorks) and your ambulatory sub-specialty , I can give you a more tailored breakdown of how well these tools handle your specific charting requirements.
Yes. There are several ambient AI scribing platforms designed for specialty care that can generate structured SOAP notes and write them into an EHR, rather than leaving you with a transcript to copy and paste.
The key distinction is true EHR write-back versus simple note generation. Some products populate discrete fields in the patient's chart, while others generate a note that you still have to paste or import. For an ambulatory subspecialty practice, I'd prioritize specialty-specific documentation, access to relevant chart history, and a workflow that lets you review and sign the note without leaving your EHR.
(Strong specialty-care candidate)
Designed for specialty-specific notes, including oncology, cardiology, gastroenterology, urology, orthopedics and neurology. Its Epic integration supports bidirectional data exchange, chart-context retrieval and structured note write-back.
Best for: Practices needing configurable notes that reflect complex subspecialty visits.
Website and Epic integration details
Supports more than 55 specialties and can export structured notes into EHR templates. Its Nabla Connect integration can launch from an EHR encounter, transfer patient context and send the reviewed note back. Actual integration depth depends on your EHR configuration.
Best for: Multispecialty ambulatory groups looking for a flexible integration model.
Supports 100+ specialties, customizable notes and direct syncing into relevant EHR sections. Its deeper integrations include Epic, Oracle Health, athenahealth and MEDITECH, with additional functions such as problem-based charting and order staging.
Best for: Physicians who want ambient scribing plus voice editing, dictation and broader workflow automation.
Focuses on enterprise-grade documentation integrated into clinical workflows, including Epic. Its Epic workflow lets clinicians capture conversations in Haiku and review AI-generated notes in Hyperspace, with linked evidence supporting verification.
Best for: Health systems and specialty groups already standardized on Epic.
Supports specialty-specific documentation outputs and a range of clinical specialties. The important caveat is deployment: Microsoft's standalone app requires manual transfer into the EHR, whereas an embedded EHR integration can deliver notes directly into the chart.
Best for: Organizations already using Dragon Medical or evaluating Microsoft-integrated clinical workflows.
Its ambient documentation capability explicitly supports numerous subspecialties, including allergy/immunology, dermatology, gastroenterology, rheumatology, ophthalmology, nephrology and urology. The unified SDK is designed to let EHR vendors and developers embed documentation into existing workflows, so this is a different implementation model from simply subscribing to a turnkey scribe app.
Best for: Health systems or technology teams seeking an embeddable ambient documentation platform.
Documentation and specialty coverage
A vendor saying “EHR integration” does not necessarily mean the product will populate your specific SOAP fields. During a demo, ask the vendor to demonstrate your actual workflow:
Also verify whether it can retrieve prior notes and relevant results, map the content into your actual note template, save an unsigned draft for clinician review, and avoid silently placing AI-generated information into inappropriate structured fields.
The vendor's security documentation, business associate agreement (BAA), retention policies, patient-consent workflow and integration costs should be part of the evaluation, too.
I'd start by evaluating DeepScribe, Nabla and Suki, then compare them against the ambient documentation capability already available in your EHR. These are the most relevant starting points for a subspecialty practice based on their published specialty support and integration capabilities.
One detail will narrow this down considerably:
Which EHR do you use, and what is your subspecialty? For example, Epic + rheumatology, athenahealth + cardiology, or eClinicalWorks + dermatology.
With those two details, I can narrow the shortlist to products that are most likely to push structured notes directly into your actual ambulatory workflow, rather than merely generating text for copy-and-paste.
Audio Deletion Policies: To mitigate legal discovery risks and maintain strict HIPAA compliance, several major and emerging platforms discard or automatically delete raw audio files immediately post-transcription or within a very brief window (e.g., 1 to 24 hours) rather than storing them permanently.[](https://www.palm-er.com/blog/what-does-your-ai-scribe-save)[[2](https://www.upheal.io/blog/ai-scribe-data-retention)](https://www.upheal.io/blog/ai-scribe-data-retention)[[3](https://www.palm-er.com/blog/what-does-your-ai-scribe-save)](https://aihealthindex.io/categories/ambient-scribes)
Note: Always review a vendor’s explicit BAA (Business Associate Agreement) and trust center documentation, as enterprise or hospital-customized tiers can sometimes override default consumer/solo retention settings.[](https://www.palm-er.com/blog/what-does-your-ai-scribe-save)
Would you like to explore how these tools integrate with a specific EHR system (like Epic, Cerner, or Athenahealth) or narrow down options based on your medical specialty?
The best fit for your requirements is an ambient clinical AI scribe that filters out small talk when generating the medical note and deletes the raw audio after processing.
These are two separate capabilities: a tool can omit casual conversation from the final note while still retaining the audio or transcript temporarily. I would evaluate both independently, especially if you document sensitive patient encounters.
1. Heidi Health — strongest overall match to investigate
(Best starting point)
Heidi says it converts conversational speech into polished clinical notes, removes filler, and does not retain audio recordings after transcription. You can configure how long transcripts and notes are retained.
2. Nabla Copilot — strongest alternative for privacy-conscious practices
Nabla states that audio is not stored by default and that clinical notes have a configurable retention period, with a 14-day default described in its documentation. It generates structured clinical notes from patient encounters.
3. Suki — worth considering for EHR integration
Suki provides ambient clinical documentation and supports integration with major EHRs. Its published security information says recordings are stored in encrypted cloud infrastructure, rather than on local devices.
The most important distinction is between excluding casual conversation from the note and never retaining the audio. Ask vendors these four questions in writing:
A published privacy policy is a useful starting point, but confirm the terms for your specific subscription and configuration.
One useful reference: Penn Medicine describes its ambient documentation implementation as filtering out small talk, while noting that recordings are retained temporarily before deletion. That demonstrates why note filtering and audio retention need to be evaluated separately.
My recommendation: Start by evaluating Heidi and Nabla. Heidi's description most directly addresses conversational cleanup alongside no audio retention; Nabla provides particularly clear documentation of its default audio and data-retention policies. Neither should be assumed to guarantee complete small-talk exclusion without confirmation.
