Karunya Lakhani’s Medikno: Giving Doctors Context in a Data-Starved System

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Modern medicine runs on judgment calls made under pressure. Patients move cities, change climates, switch products and arrive at clinics without their histories in tow. Karunya Lakhani is building for that gap. As founder and CTO of Medikno, she’s developing AI systems that surface context doctors rarely have, but urgently need.

Her focus is dermatology, where the skin records environmental change more faithfully than memory ever could. The ambition is not to replace clinicians, but to reduce guesswork in a system that relies on it far too often.

From Enterprise Systems to Clinical Reality

Lakhani’s path to healthcare AI wasn’t linear. Trained as an electronics and telecommunications engineer, she began her career at Accenture, working with large healthcare data systems. Decisions were technically data-backed but far removed from everyday clinical utility.

That disconnect sharpened during her master’s in data science at the University of British Columbia, among the earliest cohorts studying AI before the discipline had meaningful presence in India. Research into clinical conversations revealed a consistent pattern: healthcare decisions are made with incomplete information, often across borders, institutions, and time.

A patient traveling from Mumbai to Pune develops acne due to changes in water, humidity, or pollution. Another moves to Delhi and experiences different skin responses altogether. Yet the dermatologist sees only the symptom, not the context. Treatment becomes trial and error.

That failure of continuity not technology pulled Lakhani into healthcare.

AI Designed for How Doctors Actually Work

Medikno is a dermatology-first AI platform built for clinical settings. At its core is India’s first indigenous dermatology-only large language model, trained on the PARAM supercomputing infrastructure. The system analyzes visual skin data and layers it with contextual signals geography, environment, lifestyle changes, and product exposure.

The result isn’t automated diagnosis. It’s structured insight. Doctors see whether environmental factors are likely contributors, whether a formulation may be aggravating a condition, or whether a change in context explains treatment resistance.

Crucially, Medikno does not prescribe to consumers. Prescriptive authority remains with clinicians. The AI supports decisions; it doesn’t replace them.

Hardware as Adoption Strategy

Healthcare adoption fails when software ignores workflow. Within three months of launch, Medikno built its own handheld dermascope with the platform embedded directly into the device. No laptops. No dashboards. Just scan and assess.

This hardware-software integration makes Medikno part of the clinical toolchain rather than an added layer. The device is currently undergoing clinical trials in collaboration with a government hospital, with ICMR validation in process. Once approved, it transitions from screening to diagnostic use.

Early Traction, Measured Expansion

Medikno has been live for three months. In that time, nine dermatology chains across Mumbai and Pune have adopted the platform, each operating multiple clinics. Doctors scan roughly 25–30 patients daily, with records automatically captured.

On the consumer side, growth is intentionally conservative. Patients whose doctors use Medikno automatically enter the ecosystem, supplemented by early organic adopters. Without direct B2C marketing, the platform has already logged 4,000–5,000 consumer users.

The logic is deliberate: direct-to-consumer healthcare burns capital quickly. Medikno prioritizes trust-led distribution through clinicians, where adoption compounds naturally.

Beyond Aesthetics: Early Signals, Earlier Action

While cosmetic insights drive engagement, Medikno longer’s -term value lies in early detection. The same AI models can flag anomalies such as melanoma well before they become visually obvious.

For consumers, this means early warnings and clear direction to seek care. For clinicians, it means intervention when treatment is simpler, cheaper, and more effective.

Hair loss, hormonal acne, and chronic skin issues often dismissed as aesthetic are reframed as data points reflecting deeper physiological patterns. Medino treats them accordingly.

Building Slow to Build Right

The company remains intentionally lean. Lakhani leads technology. Her brother, Sadanand Karna, an MIT-trained MBA with pharmaceutical experience drives business and partnerships. The team is small by design, prioritizing alignment and capability over rapid headcount growth.

This is a product-led build, not a growth-at-all-costs play.

The Larger Thesis

Medikno’s bet is understated but consequential: better healthcare decisions don’t always require more doctors or more tests just better context at the moment it matters.

In a system strained by scale and fragmentation, memory becomes infrastructure. And in medicine, remembering correctly can be the difference between guessing and knowing.

Medikno is building for that difference.