In an interview with Aditya Kandoi, Founder & CEO, Redcliffe Labs, TimesTech explores how AI, digital diagnostics, and predictive analytics are reshaping preventive healthcare in India. Kandoi discusses the company’s technology-driven approach to improving accessibility, enabling smarter diagnostics, strengthening home sample collection, and empowering patients with actionable health insights, while emphasizing that AI should augment—not replace—clinical expertise in delivering quality healthcare.
Read the full interview here:
TimesTech: How is Redcliffe Labs leveraging AI and digital technologies to transform preventive healthcare in India?
Aditya: At Redcliffe Labs, we don’t think of AI as something that replaces a doctor’s judgment. It’s there to give people and the clinicians treating them better information, sooner, so decisions get made earlier rather than later.
Take our Face Scan feature. It’s a quick wellness check that reads visible health markers like blood pressure, cardiac variability, breathing rate, stress index, pulse, and parasympathetic activity. It won’t diagnose anything, and we’re careful never to present it that way. What it does is nudge someone who might otherwise put off a check-up to actually go get one.
We’ve also rebuilt the everyday experience of getting tested. Book through the app, the website, or just on WhatsApp. Track your phlebotomist on the way to your door. Get your report digitally, look back at old reports to see how your numbers have moved, and read a Smart Report that translates the clinical jargon into something you’d understand without googling half the words.
Behind the scenes, our labs use AI-enabled Clinical Decision Support Systems, these help standardize how results get interpreted and give our pathologists a second layer of support when making a call. Paired with quality checks and automation on the lab floor, this is a big part of why turnaround times have come down without us cutting corners on reliability.
We also run large population-level studies on diabetes, heart health, arthritis, thyroid issues, vitamin deficiencies, and honestly, some of the patterns that show up are worth a lot more attention than they get. It’s one more way we try to nudge the country toward catching things early instead of treating them late.
All of this has been added up. We’re now at over 1 crore people served, across 4,000+ pin codes, with 80-plus labs we own and run ourselves and 2,000-plus collection points, no middlemen sitting between us and the patient, which is a big reason we’ve been able to keep this affordable.
TimesTech: With operations across 220+ cities and 4,000+ pincodes, what role does technology play in ensuring accessibility, scalability, and consistent diagnostic quality across diverse regions?
Aditya: Running diagnostics consistently across 220-plus cities and 4,000-plus pin codes isn’t something you can do with good intentions alone, you need the infrastructure to back it up. That’s what technology does for us here: it’s the thing that makes sure someone testing in a small town gets the same quality and experience as someone testing in a metro.
Digital booking, live sample tracking, automated lab workflows, AI-assisted decision support each piece chips away at variability and speeds up reporting. And centralized quality monitoring means we’re not relying on any one lab or any one person to hold the standard; the system does that.
On the patient side, this is what lets someone book a test from wherever they are, get their report the moment it’s ready, compare it against six months ago, and understand what a Smart Report is telling them. As we keep growing, this is the part that must keep scaling with us because accuracy and accessibility can’t be the thing that slips as we get bigger.
TimesTech: How are smart health insights and AI-led diagnostics helping patients move from reactive treatment to a more preventive and personalized healthcare approach?
Aditya: Here’s the thing about AI in healthcare, its real value isn’t in doing the doctor’s job. It’s in getting people to the doctor with better information than they’d have had otherwise, earlier than they otherwise would have gone.
Face Scan is one piece of that, a fast, visible-markers-based wellness read that gets someone thinking about prevention instead of waiting for symptoms. Our Smart Reports do something similar on the results side, turning a dense lab report into something a person can act on, and letting them see how their own numbers have trended over time.
But the piece that really closes the loop is the human one. After a report comes in, patients can talk to a doctor to understand what it actually means and get diet and lifestyle guidance built around their own numbers and not a generic advice. That combination AI is catching what a normal person might miss, and a real conversation helping them act on it, and that is what actually changes behavior. Neither piece does much on its own.
TimesTech: Home sample collection has become a major shift in patient experience. How is Redcliffe Labs using technology to make at-home diagnostics more efficient, reliable, and convenient for consumers?
Aditya: Getting tested from home sounds simple but making it reliable takes a fair amount of engineering behind the scenes. Booking must be easy, routes must be planned well so phlebotomists aren’t wasting time, and patients should be able to see exactly where their phlebotomist is on the way over.
The part we take just as seriously is what happens to the sample after it’s collected. Our phlebotomists follow set protocols, and every sample travels in a temperature-controlled bag so nothing degrades between your home and the lab. Add centralized quality checks and digital tracking on top of that, and a sample collected at your kitchen table gets treated with exactly the same rigor as one collected inside a lab.
That’s really the goal; home collection shouldn’t be a trade-off between convenience and trust. We want people to have both.
TimesTech: As healthcare becomes increasingly data-driven, how do you see digital diagnostics and predictive analytics shaping the future of patient care and early disease detection in India?
Aditya: I think diagnostics is heading somewhere different than where they’ve been for the last few decades. Instead of mostly confirming a disease someone already suspects they have, it’s going to start flagging risk before symptoms even show up, spotting patterns early enough that someone can actually act on them.
Getting there means combining data, AI, and clinical judgment rather than betting on any one of them alone. Smart Reports, Clinical Decision Support Systems, tracking a person’s health over months and years instead of one test at a time, these all move us toward that. And when you add expert consultations and lifestyle guidance on top, a test stops being a single event and starts being part of an ongoing relationship with your own health.
That shift from reactive to predictive is, I think, the most important thing happening in this industry right now.
TimesTech: What are the biggest opportunities and challenges in building a tech-enabled diagnostic ecosystem in India, especially in terms of AI adoption, data management, and healthcare accessibility?
Aditya: India has a real shot at building a diagnostic system that’s affordable, accessible, and genuinely built around prevention rather than treatment. AI and digital platforms can push early detection further, make labs run more efficiently, support the people making clinical calls, and maybe most importantly reach places that have historically been underserved.
None of that happens automatically, though. AI is only as good as the data feeding it, so we need standardized, high-quality inputs and real discipline around how these systems get built and used. Data privacy, getting different parts of the healthcare system to actually talk to each other, and earning trust from both doctors and patients these aren’t side issues, they’re the whole ballgame.
My honest view is that AI should be augmenting clinical expertise, not standing in for it. Get that balance right, backed by strong quality standards, and India can build something genuinely connected and patient-centric a system built for prevention, not just treatment after the fact.
