AI-Powered Early Dementia Diagnostics
Multimodal AI diagnostics designed to help
clinicians detect early-stage cognitive decline with confidence
Predictive Healthcare
We transform complex biomarker patterns into early, actionable clinical clarity.
Before symptoms manifest.
89.3 %
Diagnostic Accuracy
Validated precision in identifying subtle neurological markers through AI-driven voice analysis.
20 Years
Early Detection Window
Non-invasive hyperspectral retinal imaging detects preclinical signs up to two decades before overt symptoms manifest.
Triad
Multimodal AI Fusion
Synchronized analysis combining voice resonance, retinal biomarkers, and gamified cognitive assessments.
55 Mio
People affected
Currently living with dementia globally, projected to reach 139 million by 2050.
3 Seconds
Until the Next Case
A new case of dementia is diagnosed somewhere on Earth.
75 %
Undiagnosed
The vast majority of global cases go entirely undiagnosed.
3 %
Eligible for Therapy
Only 3% of symptomatic patients are currently eligible for new, disease-modifying therapies due to the lack of accessible early testing.
The Silent Crisis
Why Early Detection is Our Greatest Weapon
Dementia is one of the most critical healthcare challenges of the 21st century, amplified globally by an aging population. By the time visible symptoms appear, the underlying neurological damage has often been progressing for decades. Traditional diagnostic methods are frequently invasive, expensive, and administered too late for meaningful intervention.
At Cerebra, we utilize the Dementia Triangle framework to shift the paradigm across three core dimensions:
Diagnosis: Moving from delayed, variable detection toward precise, timely early screening.
Therapy: Transitioning from basic symptom management toward tailored, outcome-optimized therapies.
Care: Evolving from high caregiver burden toward integrated, patient-centered care pathways.
Non-Invasive Multimodal Diagnostics
Combining advanced AI with patient-friendly screening to detect early neurological shifts
Acoustic Intelligence
Vocal Pattern Analysis
Captures micro-fluctuations in speech cadence and pause frequencies to detect early signs of cognitive decline through natural conversation.
Ocular Tracking
Retinal Biomarkers
Tracks micro-vascular density and nerve layer alterations via accessible visual scans for non-invasive dementia screening.
Adaptive Interaction
Gamified Cognitive Tests
Measures subtle shifts in reaction times and problem-solving pathways to establish a comprehensive neurological health baseline.
Gamified Cognitive Games
How good is your memory?
Take our quick, interactive memory challenge to see how our gamified cognitive tests work in real time
Our Scientific Foundation
At Cerebra Laboratories, our technology is built on rigorous, peer-reviewed science.
We are addressing the critical diagnostic bottleneck in dementia care by shifting the focus from invasive, late-stage procedures to early, accessible, and multimodal AI-driven detection
-
Current disease-modifying therapies require precise early-stage biomarker confirmation, yet traditional diagnostics are invasive and costly. Our research highlights the urgent need for scalable, non-invasive screening tools that can identify cognitive decline before symptoms fully manifest.
Kamran, Q., & Baretto, P. (2026). Dementia Research in Crisis: Six Decades of Bibliometric Evidence Target: Alzheimer's & Dementia -
By combining voice biomarkers, hyperspectral retinal imaging, and gamified cognitive assessments, our platform creates a comprehensive digital phenotype. This fusion of data allows for unprecedented accuracy in early detection and subtype differentiation.
Kamran, Q., & Baretto, P. (2026). Computational Synthesis of Dementia Research for AI-Driven Training. Springer International Publishing. -
Our bibliometric analysis of over 500,000 publications reveals a critical misallocation in global research funding. Cerebra is pioneering a shift toward diagnostic technologies that directly support the mechanistic biology of emerging therapies.
Kamran, Q., & Baretto, P. (2026). Computational Meta-Science Analysis of Dementia Research. Springer - Entrepreneurship and Innovation.
Transforming Data into Dignity
Whether you are a clinician looking to integrate advanced diagnostics, a researcher exploring multimodal biomarkers, or a partner ready to scale, we invite you to join us.