Longevity by default: Building the digital rails for connected health

Why India needs full-stack health data infrastructure to extend healthy lifespan — and how the right startups can make it happen

India's path to longer, healthier lives will be built on unglamorous foundations: interoperable records, clean diagnostics, and software that makes both actionable at the point of care. Not wearables, not longevity clinics, not AI chatbots promising personalised wellness; Infrastructure.

This distinction matters because it shapes where durable value actually accrues.

The structural problem

Walk into most Indian healthcare encounters today and the experience is disorienting in a specific way: every consultation feels like the first. Paper records travel in plastic bags. Lab results arrive as unstructured PDFs, if they arrive at all. Specialists downstream of a referral know only what the patient remembers to repeat. For acute illness, this is inconvenient. For chronic disease — hypertension, diabetes, kidney decline, metabolic risk — it is dangerous. These conditions are caught early or they compound silently, and a health system that cannot reliably move a patient's history from lab to doctor to follow-up will always be late.

Lateness, in this context, is expensive in both money and years.

India is not short of ambition. The Ayushman Bharat Digital Mission (ABDM) is a serious attempt to fix this at the architectural level: a federated, consent-based backbone designed to connect records, claims and service discovery across a fragmented provider landscape. The Ayushman Bharat Health Account (ABHA) gives individuals a portable health identity. The direction is right. The gap is execution — specifically, the middleware layer that translates policy architecture into clinical workflow. Companies like eka.care are among those building this middleware layer, focusing on making ABDM functional at the point of care rather than just architecturally sound.

Why infrastructure compounds

The global shift in health systems — from episodic treatment toward continuous monitoring, longitudinal risk stratification and data-driven intervention — is not a trend driven by consumer demand. It is driven by the economics of chronic disease at scale. Catching hypertension before it becomes a stroke, or metabolic dysfunction before it becomes Type 2 diabetes, is simply cheaper than treating the downstream consequence. The leverage on health outcomes sits at the early-detection layer, not the acute-care layer.

India's opportunity is to leapfrog the legacy model the way UPI leapfrogged branch banking. UPI worked because it solved interoperability rather than competing on individual app features. The same logic applies in health: the prize is not a better patient-facing app, it is a platform on which diagnostics, care delivery and population-level analytics can compound together. ABDM provides the policy scaffolding. What the ecosystem needs now are companies that make the scaffolding load-bearing.

What we look for

From an investment standpoint, health infrastructure companies earn conviction when they demonstrate three things. First, that they are integrated into clinical workflow rather than sitting adjacent to it — clinicians adopt tools that save time, not tools that demand additional steps. Second, that their position becomes harder to displace as data and relationships accumulate — the moat in health is not a feature set, it is the trust, compliance and daily utility that come from being embedded in the system. Third, that they are building for the developer and provider layer, not just the consumer layer — because sustainable distribution in Indian healthcare runs through institutions, not downloads.

eka.care in this context

This is the frame through which we think about eka.care, a portfolio company working on precisely this infrastructure layer. Its product stack is oriented toward the workflow problem rather than the consumer acquisition problem: doctor-facing software covering records, prescriptions, and AI-assisted documentation; ABDM and ABHA integration; and a developer API layer that lets other systems plug into the national architecture.

Today, eka.care:

• More than 50,000+ doctors onboarded across India

• 1 Million+ Prescriptions created daily using EMR and VoiceAI

• 26 million+ ABHA IDs created

• 200+ developers and healthcare institutions using the API platform

• 70 million+ monthly transactions on the developer platform leveraging AI Tools

This infrastructure approach has gained recognition at the highest levels. At the India AI Impact Summit 2026, eka.care's CEO Vikalp Sahni demonstrated the company's Voice AI technology, EkaScribe, to Prime Minister Narendra Modi. The technology converts doctor-patient conversations into structured clinical documentation in real time, addressing one of healthcare's most persistent workflow challenges. Vikalp was also invited to participate in a roundtable discussion with the Prime Minister at Seva Teerth, New Delhi, exploring how AI can drive large-scale impact in healthcare delivery. The engagement underscores the strategic importance of health infrastructure in India's digital transformation and the government's recognition of companies building practical, deployable solutions at scale.

The less visible but strategically important piece is data normalisation. Most Indian medical data is not merely fragmented — it is unstructured and inconsistent in ways that make it clinically unusable at scale. eka.care addresses this by converting fragmented prescriptions, diagnostic reports, and consultation notes into structured longitudinal records. For example, converting fragmented prescriptions, diagnostic reports, and consultation notes into structured longitudinal records allows doctors to track a patient's medical history, medications, lab trends, and treatment progression over time across different clinics, hospitals, and diagnostic centers.

The value in aggregating health records lies not just in storage but in the capacity to make that data legible: to a clinician at the point of care, to a diagnostics partner correlating longitudinal results, to a population health analytics system identifying risk patterns.

Network effects in health are slow to build and hard to reverse once established. When records, diagnostics, and follow-ups flow through an interoperable system, it can help reduce unnecessary repeat testing, improve continuity of care, and enable more informed clinical decision-making over time. That is not a consumer proposition. It is an infrastructure proposition — and infrastructure is where the best health-tech companies eventually earn their keep.

The upside

India will not extend healthy lifespan by adding another app to an already crowded market. It will do so by making health data legible, portable and actionable at a billion-person scale. That requires companies willing to do the difficult, mundane work of building plumbing — and investors willing to hold them long enough for the network effects to materialise.

The unglamorous foundation of healthier ageing is clean data, moving reliably between the right hands at the right moment. Getting that right is, quietly, one of the more important infrastructure problems in Indian deep tech.