Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
The world's most advanced ambient AI clinical documentation platform for healthcare providers.
DeepScribe is a leading ambient AI clinical documentation solution designed to alleviate physician burnout by automating the medical charting process. As of 2026, DeepScribe has evolved from a basic transcription service into a sophisticated 'Clinical Intelligence' platform. Its architecture leverages a proprietary combination of Large Language Models (LLMs) and clinical rules engines to listen to patient-provider encounters in real-time. Unlike generic AI, DeepScribe is trained on millions of clinical conversations across 50+ medical specialties, ensuring high-fidelity extraction of SOAP notes and discrete data points. The technical stack is designed for deep integration within the Electronic Health Record (EHR) ecosystem, utilizing secure API hooks to populate fields directly in systems like Epic, Cerner, and Athenahealth. Its 2026 market positioning focuses on 'Heal-LLM' capabilities, which not only document visits but also suggest ICD-10 codes, identify care gaps, and automate pre-authorizations based on the recorded dialogue. The platform operates under a strict HIPAA-compliant framework with SOC2 Type II certification, utilizing edge-processing and encrypted cloud environments to ensure patient data privacy while maintaining low-latency note generation.
Uses multi-modal acoustic models to differentiate between provider, patient, and family members in a natural environment.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Parses unstructured dialogue into discrete data fields like blood pressure, heart rate, and dates for EHR entry.
Analyzes encounter text to suggest the most accurate ICD-10 and CPT codes for billing.
Applies different LLM weights and templates based on the medical specialty (e.g., Orthopedics vs. Psychiatry).
Real-time communication with EHR databases via FHIR and HL7 protocols.
Flags potential clinical contradictions or missed screenings discussed during the visit.
Allows providers to use voice commands to trigger specific templates or EHR actions.
Provider spends 2 hours after clinic 'pajama time' finishing notes.
Registry Updated:2/7/2026
Provider reviews and clicks sync
Capturing intricate physiological data and history without losing eye contact with the patient.
Inaccurate coding leading to lost revenue in fast-paced environments.