· A Philanthropic Partnership Proposal ·
AAROGYA
The Rural Health Intelligence Alliance
Building India’s first university-anchored engine for safe, validated AI healthcare — so the next medical breakthrough reaches the 900 million people its system leaves behind.
The Problem · Rural India, 2026
India's health system was never built for its villages
900M+
people live in rural India
Roughly 65% of the population — yet the doctors, beds and specialists cluster in the cities.
1 : 1,456
people per doctor nationally
Below the WHO norm of 1:1,000 — and far worse in villages, where vacancies run deepest.
3.8×
the urban–rural doctor gap
Urban India has nearly four times the physician density of rural India.
17,500+
rural specialist posts vacant
Care arrives late; disease is caught at the emergency stage; illness pushes families into poverty.
The result: late diagnosis, preventable deaths, and households pushed into poverty by illness that could have been caught early.
The Turning Point · AI, Proven Safe
A doctor gap AI can bridge — but only if it is proven safe
A 600,000-physician gap
India cannot train doctors fast enough to close the shortfall — but intelligence can travel where doctors cannot.
Demand is already proven
47 crore+ teleconsultations on eSanjeevani since 2019 show rural India is ready — the gap is capability, not demand.
AI is arriving unproven
Models trained on Western data drift in Indian settings: hallucinated dosages, faulty reasoning and demographic bias are documented.
No safety infrastructure
India has no standardised benchmarking, no silent-deployment testing, and no validated pathway from lab to real-world use.
Why Shiv Nadar IoE
Next door to the problem — and built to solve it
India’s youngest Institution of Eminence · NIRF #57 (University, 2025) · 286-acre campus · Home of the AI Centre · Rooted in Dadri, Uttar Pradesh
Interdisciplinary by design
Govt. of India Institution of Eminence · NIRF #57 (University, 2025) · four schools on one campus working across disciplines.
Surrounded by those we serve
Dadri & Gautam Buddha Nagar, UP — rural primary health centres minutes from the campus gate.
Governance & transparency
Quarterly impact reporting, clear milestones, co-branding and independent verification built in.
The AI engine is already running — not a plan on paper
AI-led
drug discovery with industry partners
1st
CTRI-registered AI platform trial in India (planned)
MOOVE
global AI-evaluation platform, localised for India
3,500+
students in residence; 250+ global faculty
The Vision · What Your Gift Changes
What changes when intelligence reaches the village
See more, earlier
AI-assisted screening for anaemia, TB, diabetes and maternal risk — at the doorstep, not the district hospital.
A copilot for every ASHA
India's 1M+ community health workers gain a validated AI assistant in Hindi — triage, referrals and follow-up.
Reach where doctors can't
A campus-anchored tele-triage hub links village screening points to physicians and specialists in real time.
Predict, don't react
Village-level surveillance flags disease clusters and seasonal risks before they become outbreaks.
Our Solution · AAROGYA ("Well-being")
Six components of safe AI healthcare for rural India
Validation Pipeline
A three-phase, ethics-supervised pipeline that carries an AI tool from lab (TRL 4) to deployment-ready (TRL 7) — with hard Go / No-Go gates.
MOOVE Platform
The world's most structured healthcare-AI evaluation platform, deployed internationally and now localised for Indian clinical practice.
Screening & Triage
Decision support for TB, diabetic retinopathy and maternal risk — validated for the very people it will serve.
ASHA & CHW Training
Dedicated training for community health workers in the safe use of AI tools — delivered in Hindi.
Clinical Partnerships
District hospitals in Gautam Buddha Nagar, Bulandshahr and Hapur — data-sharing and advisory clinicians.
Evidence & Policy
Peer-reviewed publications and PrAImaan-aligned governance — India's evidence base for safe health AI.
Every dollar multiplied. Aligned with India’s national AI-safety framework and matched by government (ANRF) and industry co-funding.
Safety First · Tested Like a Medicine
Three phases, three gates — only proven tools reach patients
Expert Review · Year 1
Doctors stress-test every AI tool against 50+ real clinical scenarios, localised for Hindi and Indian practice — before it ever meets a patient.
Shadow Testing · Yrs 2–3
Under full ethics approval, the AI runs silently alongside real care — watched and measured, but never influencing a single decision.
Clinical Trial · Yrs 4–5
A CTRI-registered trial with independent safety monitoring and doctors in charge at every step — the same rigour as a new medicine.
Only tools that pass every gate reach patients
This is what your gift protects: the promise that no unproven algorithm will ever practise medicine on the people who can least afford its mistakes.
The Work Plan · A Five-Year Roadmap
What happens, year by year — with clear ownership and gates
Year 1
Set-up & MOOVE localisation
AI CentreEthics clearances & data pipeline
IRB · ITExpert / hypothetical evaluation
Clinical panel
Year 2
Silent (shadow) evaluation begins
PI + hospitalsASHA & CHW training in Hindi
Training unit
Year 3
Shadow evaluation concludes
PI + hospitalsVillage screening & tele-triage hub
Field team
Year 4
CTRI-registered clinical trial
PI + DSMC
Year 5
Predictive surveillance & scale-up
Data sciencePublications, policy & playbook
All
The Impact Matrix · What We Will Deliver
Every outcome tied to a metric, a target and a way to verify it
| Outcome area | Year 1–2 | Year 3 | Year 5 target | How verified |
|---|---|---|---|---|
| AI systems validated | 1 in evaluation | 1 in shadow | 1+ validated to TRL 7 | CTRI trial + audit |
| People screened | 5,000 | 25,000 | 100,000+ villagers | Camp & PHC records |
| ASHAs / CHWs trained | 50 | 300 | 1,000+ using copilot | Attendance + usage logs |
| Tele-triage consults | 1,000 | 10,000 | 50,000+ completed | Platform dashboard |
| Time to diagnosis | baseline set | −25% | halved for target conditions | Baseline–endline study |
| Trained AI-safety evaluators | 5 | 12 | 20+ across the system | Certification records |
| Peer-reviewed publications | 1 | 3 | 4–6 papers + playbook | Journal DOIs |
Honest reporting. Baseline–midline–endline studies, an independent evaluation partner and a live donor dashboard — failures reported as openly as wins.
Where We Grow · Nearby First, Then India
Start next door. Prove it. Then scale it for India.
Neighbourhood · Yrs 1–2
Partner villages across Dadri block, Gautam Buddha Nagar — AI screening camps, ASHA copilot pilots and a campus tele-triage hub, all inside the validation pipeline.
District & UP · Yrs 2–4
Rollout through PHCs and CHCs with district hospitals in Gautam Buddha Nagar, Bulandshahr and Hapur; predictive surveillance across blocks; a state health partnership.
India · Yrs 4–5
Open, peer-reviewed deployment playbooks and validated tools that states, NGOs and co-funders replicate — from 25 villages toward 900 million.
Every expansion step is gated by evidence. Nothing scales until it has passed validation with the communities it serves. Targets are set jointly with district and state partners.
The Investment · A $2.5M, Five-Year Program
Where the money goes — and how it tapers as the centre sustains itself
$2.5M
over five years
- People & training40%
- Validation & trials29%
- Field & tele-triage20%
- Platform & data11%
- People & training
- Validation & trials
- Field & tele-triage
- Platform & data
Relative allocation by year ($K).
Figures exclude the targeted 1:1 ANRF/industry match. Funds ring-fenced under an MoU with milestone-linked release and independent annual audit.
Risk & Mitigation · Eyes Open
The risks we have named — and how each is managed
Trial or regulatory delay
CTRI registration and CDSCO review can slip. Go/No-Go gates and shadow-testing years de-risk the trial before it starts; ethics filings begin Year 1.
Match funding shortfall
The 1:1 ANRF/industry match is a target, not yet fully committed. Milestone-linked release means the core program runs on the gift alone if the match slips.
Validator independence
The industry partner supplies systems the centre also validates. An independent ethics board, blinded shadow testing and published protocols wall off evaluation from the vendor.
Data privacy (DPDP Act)
Village health data is sensitive under India's DPDP Act, 2023. Consent-based collection, on-campus storage and de-identification are built into the pipeline from Year 1.
ASHA adoption
Tools fail if frontline workers don't trust or use them. Hindi-language design, in-person training and usage tracking make adoption a measured, funded outcome.
Model safety in the field
Models can drift or err on unseen Indian cases. Silent deployment, human-in-the-loop review and hard Go/No-Go gates keep unproven tools away from patients.
No surprises. Every risk above is reviewed quarterly with the donor and reported on the live dashboard — including the ones we are still working to close.
Your Partnership · What You Give, What You Get
Four ways to give — each with real recognition and access
Visionary
$1M+
You give
Name the AAROGYA program and co-design its scale-up.
You receive
- Advisory board seat
- Annual campus welcome
- Named recognition on all outputs
- Quarterly board briefings
Champion
$250K+
You give
Fund an entire program phase end to end.
You receive
- Named phase recognition
- Biannual private briefings
- Site visit & field access
- Early view of research
Benefactor
$50K+
You give
Train an ASHA cohort or fund a village cluster for a year.
You receive
- Named cohort / cluster
- Impact story + data pack
- Live donor dashboard
- Annual partner summit
Friend
$10K+
You give
Sponsor village health-screening camps.
You receive
- Live donor dashboard
- Annual impact report
- Recognition in reporting
- Partner summit invite
Built to Last · Team & Sustainability
World-class expertise — and a centre that pays for itself
Leadership
Prof. Mary-Anne Hartley
Lead PI · MOOVE architect · Director, AI Centre
Prof. Chris Bain
AI Healthcare Expert
Robin Abrams
Ex-Director, HCL Technologies
Dr. Siddharth Savyasachi Malu
AI Centre of Excellence · PI, AI systems & clinical validation
Clinical Advisory Panel
Dr. Mayank Garg (WHO) and practising clinicians across UP district hospitals and internationally
Self-sustaining by design
Validation services
From Year 2, contract validation for AI developers seeking India-specific safety evidence, plus CDSCO regulatory-submission support.
Training programmes
Workshops that build India's AI-safety evaluation workforce — for hospitals, agencies and health-tech firms.
Industry partnership
A committed technology partner provides the AI systems under validation — with cash co-funding and deployment access.
By Year 4, non-grant revenue covers half of operating costs. Grant dependence tapers. Impact compounds. Your gift builds an institution, not a project.
How We Work · From First Call to the Field
From first call to a live program — quickly
Discovery
One call to understand your philanthropic goals, geography and horizon.
Co-design
We shape the gift — phase, scale, recognition and milestones, together.
MoU & US giving route
A single point of contact; a compliant US–India structure from day one.
Launch & reporting
The programme goes live, with quarterly impact reports to you and your board.
One door, one owner. A single point of contact in the Office of the Vice-Chancellor manages your partnership end to end — no committees to chase.
Join us
Bring healing home
Help build the safety layer that lets India’s AI revolution reach the last mile — validated, trusted, and Indian by design.
Saurabh Suman
Lead, Fundraising & Strategic Partnerships · Office of the Vice-Chancellor
saurabh.suman@snu.edu.inShiv Nadar Institution of Eminence, Delhi-NCR
Tax-deductible for US donors via a US 501(c)(3) partner such as CAF America — compliant end to end.