Healthcare AI in India feels like it's either overhyped nonsense or genuinely life-saving, and telling the difference is really hard. How do people actually evaluate this stuff?

Been thinking about this a lot lately and wanted to get some honest opinions from people who've actually worked in or around healthcare tech in India.

The space is genuinely confusing. On one hand, you have real, serious work happening — AI systems that are actually running inside hospitals, detecting things that human pathologists miss, reducing diagnostic turnaround times from days to hours. Stuff that is measurably saving lives and reducing costs in a healthcare system that desperately needs both.

On the other hand, you have a massive amount of "AI for healthcare" that is basically a dashboard with some statistics on it. Or a WhatsApp bot someone calls an AI system. Or a company that has done one pilot at one small clinic and is now claiming to be transforming Indian healthcare.

A few things I think genuinely separate the real from the noise

Clinical accuracy standards are completely different from normal tech

In e-commerce, 90% model accuracy is something to celebrate. In healthcare, it means 1 in 10 patients gets a wrong result. The bar is categorically different and any company that doesn't talk about this distinction upfront is either naive or deliberately vague. Real healthcare AI companies obsess over false negative rates, sensitivity, specificity — not just overall accuracy.

Regulatory compliance is where a lot of companies quietly fail

CDSCO clearance in India, FDA clearance for anything touching US markets, CE marking for Europe — these are not optional. But getting them is genuinely hard and time-consuming. A lot of AI health-tech companies in India are operating in a grey zone where their product is being used clinically without proper clearance. This is a massive risk that doesn't get talked about enough. Hospitals adopting these tools are also taking on liability they may not fully understand.

The EHR integration problem is massively underrated

Every hospital in India runs on different systems. Some still use paper. Getting AI to actually work inside existing clinical workflows — not as a separate tool that creates more work for doctors, but as something genuinely embedded in how they work — is an enormous technical and operational challenge. Most companies demo their product in isolation. The hard part is what happens when it needs to talk to a 15-year-old hospital management system.

There's a real difference between product companies and development partners

Some companies build their own products — a diagnostic tool, a radiology assistant, a lab automation system. Others build custom AI for healthcare organisations — hospitals, health-tech startups, pharma — and are essentially your development partner. Both are valuable but they solve completely different problems. A lot of confusion happens when organisations approach a product company expecting a custom development partner or vice versa.

The compliance-first vs feature-first divide

This one is subtle but important. Some companies design compliance into the architecture from day one — data governance, audit trails, access controls, HIPAA-aligned data handling are built in before the first feature. Others bolt it on later. The second approach works fine until it doesn't — and in healthcare, when it doesn't, the consequences are serious.

Has anyone here actually evaluated or deployed healthcare AI in India? What did you find most difficult? And has anyone seen examples of implementations that actually worked well at scale- not just at pilot stage?