muunai - 2026 Pricing, Features, Reviews & Alternatives

muunai is a cloud-based, AI-assisted medical documentation platform designed for individual physicians, outpatient medical practices, and larger healthcare organizations, with a primary focus on the German-speaking healthcare market. The platform transcribes patient-clinician conversations in real time and automatically generates structured clinical reports, ICD code suggestions, and EHR-ready entries from conversation audio. Documentation is delivered directly into the EHR with a single click, and patient conversation recordings are deleted after report generation, with all data processed on EU-based infrastructure in compliance with GDPR.

The platform supports a broad range of clinical workflows across specialties including general practice and ENT. Clinicians can configure custom report templates with predefined sections and keyword-triggered text blocks to match specialty-specific or practice-specific documentation standards. A smart chat interface allows editing of generated reports, querying of encounter details, and searching of medical literature without leaving the documentation environment. Visit preparation is supported through AI summarization of incoming doctor letters and documents, which are fed as context into new encounter documentation. A free dictation add-on extends speech input to any text field on Windows and Mac desktops, and a native iOS app supports on-site documentation during home visits with on-device report generation.

muunai adapts continuously to individual clinician style and language through feedback and correction loops, ensuring that generated documentation reflects each clinician's preferred terminology and structure. Team collaboration features and deep EHR integration, including a dedicated integration with t2med, make the platform suitable for both solo practitioners on the Professional plan and larger clinical organizations on the Enterprise plan. Dynamic checklists generated during conversations help ensure documentation completeness across encounter types.