BrainSightAI

BrainSightAI is an advanced neurotechnology platform that leverages AI, ML, and 3D visualization to create detailed connectomic profiles of the brain, capturing both its structural and functional patterns. Addressing the critical gap in neuropsychiatric diagnostics and neurosurgical planning, BrainSightAI moves beyond traditional reliance on self-reported symptoms and basic structural imaging by offering non-invasive, high-resolution insights into brain connectivity. This enables early detection of disorders like dementia or schizophrenia, and more accurate pre-surgical assessments for conditions like brain tumors. Integrated into a user-friendly SaaS platform, clinicians receive objective, personalized reports that support evidence-based decision-making. The workflow includes seamless processing of MRI data into interactive, 3D brain maps with clinically relevant markers, significantly reducing time and cognitive burden for doctors. By enhancing diagnostic accuracy and planning precision, BrainSightAI aims to reduce the global burden of CNS disorders and improve patient outcomes at scale.

Key Differentiators

• Only solution in mental health combining AI on functional MRI, structural MRI, and digital phenotypes
• Among the very few globally using rs-fMRI; enables individual-level insights instead of group-level averages
• Traceable AI that allows clinicians to question and interpret results, increasing trust and adoption
• Patented data-processing pipeline with report turnaround within 24 hours
• 3D visualization engine for enhanced clinical interpretability
• Cloud-based SaaS platform for simple, scalable deployment
• Aligned with the World Psychiatry Association’s framework for future psychiatry
• Covers the full care continuum: from early triaging to diagnosis and treatment planning
• Supports all stakeholders: patients, caregivers, clinicians, hospitals, pharma, and insurers

Measurable Impact / Improved Outcomes

• Enables 90X earlier screening and 10X earlier confirmation
• Substantial sensitivity improvements over competitors for clinical-grade accuracy
• Improved treatment personalization, leading to better patient outcomes
• Faster pre-surgical planning and recovery forecasting
• Accelerated patient recruitment for clinical trials