Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
AI-powered speech analysis for early-stage cognitive impairment screening.
CognoSpeak is a clinically-validated medical AI platform developed by researchers at the University of Sheffield, designed to streamline the screening process for Alzheimer’s disease and other forms of dementia. The system utilizes a virtual agent to conduct a standardized interview, capturing audio data that is subsequently analyzed using advanced Natural Language Processing (NLP) and acoustic signal processing. Unlike traditional pen-and-paper tests like the MMSE or MoCA, CognoSpeak provides a non-invasive, objective analysis of linguistic markers, syntax complexity, and paralinguistic features such as hesitation and pitch variation. In the 2026 market landscape, CognoSpeak serves as a critical triage tool for primary care physicians, significantly reducing the bottleneck in neurology clinics by identifying high-risk patients who require specialist intervention. The technical architecture is built on proprietary machine learning models trained on extensive clinical datasets, ensuring high sensitivity and specificity in detecting early cognitive decline. It integrates into healthcare workflows via FHIR-compliant APIs, making it a scalable solution for population-level cognitive health monitoring.
Analyzes syntactic structures and vocabulary richness to detect subtle 'word-finding' difficulties (anomia) associated with early-stage Alzheimer's.
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.
Measures micro-fluctuations in pitch, jitter, and shimmer, alongside pause duration and frequency.
A standardized, non-judgmental AI interviewer that ensures consistency in testing environments across different clinics.
Deep integration with Electronic Health Records for seamless results delivery into patient charts.
Cross-lingual AI models that can analyze cognitive health in multiple languages without local re-normalization.
Configurable risk-scoring algorithms that flag 'red-alert' cases for immediate neurology follow-up.
Tracks speech changes over months/years to determine the rate of cognitive decline or treatment efficacy.
GPs often lack the time for extensive memory testing, leading to over-referral or missed early cases.
Registry Updated:2/7/2026
Referral decision is made based on objective data.
Identifying patients at the exact prodromal stage of Alzheimer's is difficult and expensive.
Rural patients cannot easily travel to neurology centers for monthly check-ups.