Aarogya Aarohan

Overview

Aarogya Aarohan is an AI-powered mobile and web platform developed by Triveous as part of the AI:COE consortium, led by the Indian Institute of Science (IISc) in partnership with ARTPARK, Biocon Foundation, AIIMS, and other healthcare and research institutions. The platform is designed to enable frontline health workers (FLWs) to screen for potentially suspicious oral lesions in underserved communities, with seamless coordination between field teams, remote specialists, and researchers.

Built for low-resource and connectivity-constrained settings, the platform demonstrates how thoughtful design, robust engineering, and responsible AI can extend the reach of preventive healthcare services to India’s most remote populations.

The Challenge

India bears one of the world’s highest burdens of oral cancer, largely due to late-stage detection. In rural and semi-urban regions, screening is hindered by the lack of trained professionals, inconsistent processes, and poor digital infrastructure.

Frontline health workers often rely on manual paper-based records, making it difficult to ensure consistency, follow-up, or centralized reporting. Connectivity issues further complicate the ability to share patient data or escalate cases to remote specialists for review. There was a need for a digital solution that could work in these constraints, empower field workers, and enable timely intervention.

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Our Approach

Triveous designed and developed an offline-first, mobile and web-based platform to support screening and triage workflows — from field-level data capture to remote case review — all built to align with national screening guidelines and data privacy standards.

The mobile app enables FLWs to capture structured patient details, habit history, and oral images, even in fully offline conditions. A guided step-by-step workflow ensures adherence to protocol, while auto-syncing ensures data continuity when connectivity returns.

The app also integrates AI-based assistive tools that analyze captured images and flag potentially high-risk lesions for review. These tools support FLWs in triaging cases more confidently and consistently, without replacing human judgement or offering a clinical diagnosis.

Remote specialists access a secure web dashboard that presents patient history, images, and AI-supported screening classifications. They can review cases and provide next-step actions like requesting retakes or recommending hospital referrals. The system also includes robust role-based access, audit logs, and support for regional languages.

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Key Capabilities
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• Offline-Capable Mobile App: Enables health workers to screen patients in fully offline settings with secure auto-sync.
  
• Guided Workflows: Step-by-step process aligned with national oral health screening protocols.
  
• AI-Assistive Tools: Embedded models help flag high-risk lesions for further review, supporting early triage.
  
• Specialist Dashboard: Structured data and images for review and follow-up decisions.
  
• Intelligent Annotation Tools: Randomized labeling for AI model validation and improvement.
  
• Multi-role Access: Built for health workers, specialists, program admins, and researchers.
  
• Regional Language Support: Localized interfaces for usability in diverse linguistic settings.‍
• Governance-Ready Infrastructure: Patient data anonymization, audit trails, and compliance with national data privacy frameworks.

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Impact

Aarogya Aarohan enabled rapid screening and triage in rural areas, often in under five minutes per patient — empowering FLWs to screen large volumes efficiently while escalating high-risk cases to specialists. Its scalable and modular architecture is ready for national deployment and has already demonstrated value in bridging gaps between rural field teams and urban healthcare infrastructure.

The platform's assistive AI tools helped increase frontline confidence and consistency, while still ensuring expert human oversight. With its robust data systems, it also contributes to building structured datasets for future research and public health planning.

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Triveous’ Role

• Led end-to-end product design, backend systems, and mobile development
  
• Conducted in-field research to understand real-world screening workflows
  
• Developed AI-human workflows in close collaboration with clinicians and researchers
  
• Delivered secure, scalable infrastructure aligned with Digital Public Infrastructure principles
  
• Played a key role in one of India’s first AI-powered public health screening platforms
  
  

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Conclusion

Aarogya Aarohan is not just a digital product — it's an example of what’s possible when health, research, and technology ecosystems collaborate with purpose. Designed to extend the reach of frontline health workers and specialists alike, it offers a powerful model for how AI and inclusive design can improve access to early screening and quality care in underserved communities.

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