Sunoh for Web

Turn clinical conversations into polished records

Sunoh is a browser-based AI tool built for healthcare teams to convert spoken or written clinical conversations into complete, structured documentation. It reduces the time clinicians spend on paperwork so they can devote more attention to patient care.

Key benefits for clinical teams

• Saves clinicians time by automating note creation and reducing manual entry.
• Improves the consistency and completeness of clinical documentation.
• Helps capture important clinical details reliably from dialogues and encounters.
• Streamlines workflows so teams can spend less time on admin tasks and more with patients.

How the system works

Sunoh applies advanced natural language processing to healthcare conversations, identifying and extracting the most relevant clinical facts. It then organizes those findings into standardized note formats clinicians can review and edit. This automated summarization aims to preserve critical context while reducing the burden of drafting records from scratch.

Access model and cost overview

Sunoh is offered via a subscription service that unlocks its full feature set. Different tiers typically provide varying levels of access, such as transcription limits, integrations, and support options, so organizations can choose a plan that matches their documentation volume and budget.

Integration and user experience

The interface is designed for quick adoption, allowing smooth incorporation into existing clinical workflows and electronic health record systems. Settings and templates can be adjusted so output matches an organization’s documentation standards and reduces the need for manual reformatting.

Alternatives worth reviewing

• Cliniscribe — enterprise-focused paid option with robust EHR connectors.
• OpenNote — free or low-cost solution aimed at small clinics and solo practitioners.
• Herodot — paid platform recommended by some organizations for clinical summarization.
• NoteAssist — offers a trial and tiered subscriptions for mixed clinical teams.