Gabify Secures $175K to Scale AI Screening for Autism and ADHD in India

Gabify funding highlights growing use of AI in early diagnosis of speech and neurodevelopmental disorders, where access and screening delays remain major challenges.

Gabify, an India-based health technology startup, has raised $175,000 in a pre-seed funding round led by Inflection Point Ventures, as it looks to scale its AI-powered platform for early screening of neurodevelopmental disorders.

The platform focuses on identifying conditions such as autism and ADHD at an early stage, using a combination of voice and visual analysis. By evaluating speech patterns, facial expressions, eye movement and behavioral signals, the system aims to assist clinicians in detecting developmental concerns faster and more consistently.

Gabify’s approach combines AI-driven analysis with human oversight. Its human-in-the-loop model ensures that clinical professionals review AI-generated outputs, addressing reliability concerns that often limit adoption of automation in healthcare settings.

The funding will be used to strengthen clinical validation, enhance the platform’s capabilities and expand the team as the company prepares for broader deployment.

Gabify is positioned as an end-to-end SaaS platform for speech and neurodevelopmental care, integrating screening, assessment and therapy management within a single system. The platform leverages a dual-AI architecture combining voice and vision analysis, while remaining adaptable to low-bandwidth environments and multilingual use cases, making it suitable for deployment across both urban and rural settings.

The company has also received support through government-backed initiatives such as the Nidhi Seed Support Scheme, highlighting increasing institutional interest in digital health solutions aimed at early intervention.

The development comes at a time when early diagnosis of neurodevelopmental conditions remains a major challenge in India, driven by limited specialist availability and long evaluation timelines. As demand for early intervention grows, AI-based screening tools are emerging as a way to bridge access gaps and improve outcomes. More broadly, the move reflects a shift in healthcare AI, where success is increasingly tied not just to model capability, but to clinical integration, trust and scalability in real-world environments.

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