AI Medical Scribe - Turning Patient Conversations into Clinical Documentation

It is both. The scribe runs in dictation mode, where you narrate findings directly, and in ambient mode, where it listens to the natural back-and-forth of the visit and drafts from the conversation itself. The same model handles both, so you can dictate the exam and let ambient capture handle the patient dialogue in a single encounter. Dictation transcribes what you speak; ambient scribing captures the whole visit and separates speakers, so the draft note forms while you are still with the patient rather than after they leave.

Speech is transcribed in real time with the model tuned for clinical vocabulary: drug names, dosages, anatomy, lab values and the abbreviations clinicians actually use. Phrases like "BP one forty over ninety" and "started on lisinopril ten milligrams" are transcribed as clinical content, not guessed at phonetically. Accuracy depends on audio quality, background noise and speaker accent, and low-confidence passages are flagged for a closer look. Because a clinician reviews and signs every note, accuracy is verified at the point of documentation rather than assumed.

Yes. We can embed the dictation and ambient capture directly into your telehealth platform or EHR software, so clinicians document inside the tools they already use instead of running a separate app. For product teams and EHR or SaaS partners, that means the capture-to-chart flow is built into your product rather than bolted on beside it, with the model, audio pipeline, and EHR write-back wired into your stack. As an embedded engineering team, we build that integration and keep running it in production rather than handing over a tool and walking away.

It means building the capture-to-chart workflow around your systems rather than fitting your practice to a fixed product. That covers ambient and dictation capture, real-time transcription tuned to your specialty terminology, speaker separation, a structured draft note, and write-back into your EHR through FHIR, HL7 or a structured copy step. We are an embedded AI engineering team, so we build the scribe, integrate it with your EHR and visit formats, and keep running it in production once it ships.

Yes. The scribe is AI clinical documentation software that runs the full flow from spoken encounter to signed note in the EHR. It captures the visit, transcribes it, drafts a structured note sorted into Subjective, Objective, Assessment and Plan, and writes the signed note back through FHIR or HL7 based integration. Capture, transcription, structured drafting and write-back run as a single workflow, so nothing is re-keyed between systems.

This is a build-versus-buy decision. Off-the-shelf scribes give you a packaged product on the vendor's roadmap, integration list and data terms, which is the fastest path when a standard fit works for you. A custom build fits the capture modes, specialty terminology, EHR write-back path and data-handling rules to your environment, and you own how it evolves. We do not claim feature parity or make comparisons on specific competitor capabilities. The honest framing is a packaged product versus a scribe built and run around your workflow by an embedded engineering team.

Yes. Signed notes write back into major EHRs through standards-based integration, so documentation reaches the patient chart without re-keying. For systems with FHIR APIs, including Epic, Oracle Health (Cerner), athenahealth and Veradigm, notes are written back through FHIR. Where an organization runs on HL7 messaging or an interface engine, the scribe connects through that path instead. When direct write-back is not available, the finalized note is delivered as a structured block ready to paste into the chart, so you are never blocked from getting the note into the EHR.

Yes. The scribe is built for solo practitioners and small practices as well as hospitals and specialty centers, and it reduces documentation time without adding staff. A private practice gets draft notes ready during or right after the visit, so a clinician can capture late and weekend visits without rostering an extra scribe. It scales from a single provider to a larger practice while keeping the same review-and-sign workflow.

Rollout is designed for low disruption across existing clinical workflows. Our onboarding team handles implementation, EHR integration and training, and we tune the model to your terminology during onboarding, so clinicians can start using the scribe in days rather than months. Because the clinician always reviews and signs, adoption does not ask providers to trust an unedited note. It slots into how they already document and takes the typing off their plate.

The scribe is configured around your specialty's terminology, documentation style and clinical workflow, and we tune to your vocabulary during onboarding. It is built for high-volume, specialty-based practices where accuracy is critical, and it interprets complex terms, dosages and abbreviations in context. This keeps notes consistent and specialty-aligned across a broad range of care settings rather than forcing one generic template.

It takes documentation off the clinician's plate by capturing the encounter, drafting a structured note and handing it back for review, so providers stay with the patient instead of the keyboard. Lower after-hours charting load is one of the most consistent reasons clinicians adopt an ambient scribe. Less time reconstructing notes at night is the clearest signal that a scribe is working in a practice.

Yes, and nothing reaches the chart on its own. Every note is a draft until a clinician reviews it, edits anything that needs it, and signs, and only then does it write back to the EHR. The scribe supports the documentation workflow; it does not diagnose, make clinical decisions or document on its own authority. Low-confidence passages are flagged for a closer look before sign-off, so a human owns what reaches the record.

Yes. The scribe captures audio from a telehealth video session or a phone visit the same way it captures an in-person consultation and drafts a structured note from it. You can also upload a recording from an encounter that happened outside the live workflow and document it afterward. The same review-and-sign workflow covers in-person, remote and asynchronous care.

The model separates clinician speech from patient speech, so a symptom the patient describes is not logged as a clinical finding and each voice routes into the right part of the note. Clear audio gives the best results: heavy background noise, crosstalk or a poor microphone can lower transcription accuracy. That is one reason every draft is reviewed before sign-off rather than filed automatically.

For systems with standards-based APIs, including Epic, Oracle Health (Cerner), athenahealth and Veradigm, signed notes are written back through FHIR. Where an organization runs on HL7 messaging or an interface engine, the scribe connects through that path instead. When direct write-back is not available, the finalized note is delivered as a clean structured block ready to paste into the chart. The exact path depends on your edition and the integration access your organization has enabled, and we confirm it during onboarding.

The scribe is strongest with English clinical speech and handles a range of accents, though very strong accents or noisy audio can affect accuracy. Support for additional languages depends on your configuration. Because the clinician reviews and signs every note, anything the scribe mishears on a heavy accent is caught and corrected before it reaches the chart.

Audio, transcripts and patient information are encrypted in transit and at rest, and access is controlled. Audio handling is configured to your organization's policies, and retention can be set to match your requirements, including capture-and-discard workflows where audio is not kept after the note is drafted. We build controls that support your HIPAA and data-handling obligations and can operate under a BAA; your practice remains the covered entity. We support your compliance requirements rather than claiming certification on your behalf, and we confirm the exact security and retention setup during onboarding.

They are two halves of the same workflow. The AI Medical Scribe owns capture and the documentation flow: listening to the visit, separating speakers, transcribing accurately and writing the signed note back to your EHR. AI SOAP Notes owns the output format: organizing that encounter into a clean Subjective, Objective, Assessment and Plan note aligned to your specialty. Most clinics use them together.