Best Telemedicine App in India: Auditing What AI Recommends and Why

This article is for founders and growth leads at Indian telemedicine and digital-health apps. When a patient asks an AI assistant for "the best telemedicine app in India", the assistant produces a short list. Your product is either on it, described accurately, or it is not. This post shows how to find out which, and what to do next.

It is a teardown of the method rather than a report of results. We are not publishing a ranking of apps, because answers differ by engine, by day and by how the question is phrased, and a single snapshot would mislead. What follows is the audit design we would run, the log you need, and the rules for reading it.

It assumes you already have a working site and app-store listing. If your site still needs the basics, start with our piece on telehealth website design, which covers page structure and booking flow. This article covers what happens after the page exists: whether machines can find it, describe it and recommend it.

The reference point is a free government service

Any honest audit starts with context. India's national telemedicine service, eSanjeevani, has passed 50 crore teleconsultations, according to All India Radio's report from October 2026. An AI assistant answering "best telemedicine app in India" will often name it, because it is large, public and widely written about.

For a private app, that changes the competitive question. You are rarely going to be named as a replacement for a free public service. You are more likely to be named for something specific: a specialty, a language, evening availability, second opinions, a follow-up programme for a chronic condition, a corporate arrangement. The audit should test those narrower prompts as much as the broad one.

What you are auditing

Four things, in this order:

1. Recognition. Does the assistant know your brand exists, and does it describe it correctly when asked directly?
2. Inclusion. Are you in the list when the question is about your category, specialty, language or city?
3. Attributes. When you are named, what reasons are given: price, speed, specialties, languages, doctors, regulation? Are they true and current?
4. Sources. Which URLs does the answer cite, or appear to draw on, and who owns them?

Recognition and attributes are about your own data. Inclusion and sources are about the wider web.

Design the prompt set

A useful set is 40 to 60 prompts, grouped so that you can see where visibility breaks.

Write each prompt in a patient's voice, not a marketer's. Add persona variants where it matters: a parent in a tier-two city, an NRI arranging care for parents in India, an HR manager comparing options for staff.

Run protocol

Answers vary, so a single run proves little.

• Run every prompt on each engine you care about. Common choices are ChatGPT, Google's AI Mode and AI Overviews, Gemini, Perplexity and Copilot.
• Record whether web search or browsing was on, whether you were logged in, the device, the city setting and the date.
• Repeat each prompt at least three times and note how stable the list is.
• Re-run the full set monthly, and after any major site or listing change.
• Use fresh sessions without personalisation where possible. Do not train the assistant by chatting about your brand beforehand.

Never submit patient details, even invented ones that resemble a real person, into these tools.

The log schema

Whether you use a spreadsheet or a database, capture the same fields so that months can be compared.

• prompt_id, prompt_text, group, language
• engine, mode (search on or off), run_no, run_date
• brand_listed (yes or no) and position (if a list)
• brand_description (as written by the engine) and description_accurate (yes, partly, no)
• attributes_stated (price, speed, specialties, languages, regulation)
• competitors_listed (ordered)
• cited_urls and source_type (own site, app store, directory, news, forum, video, government)
• harmful_or_wrong_claim (for example, a claim that you offer something you do not)
• notes

If you want a ready-made tracker, a tool such as AiLLMz can log these runs on a schedule. A spreadsheet is enough for the first month.

How to read the results

The log is only useful if you act on patterns. These are the common ones and what they usually mean. We describe them as hypotheses to test, not as findings about any particular app.

Look at the sources column before anything else. Peec AI's study of the most-cited domains across AI answers found Reddit, YouTube, LinkedIn, Wikipedia and Forbes among the most frequent. That is a general finding across many topics, not a health-specific one, so check your own log. If your health-category answers cite listicles, app-store pages or review sites, those become your outreach and accuracy list.

What actually moves recommendation lists

Nobody outside the engines can promise a ranking. These are the levers that are within your control and have a sensible rationale.

A clear "what we are" page. One page that states what the service is, which specialties and languages it covers, who the doctors are, how consultations work, what it costs and how to complain. Plain sentences are easier for both a person and a model to quote.

Consistent identity. The same legal name, description and website link on the app store, your site, social profiles and directory entries. Our AI search optimisation guide goes into entity consistency.

Regulatory clarity. The Telemedicine Practice Guidelines issued by the Ministry of Health and Family Welfare in 2020 set the framework for consultations by registered medical practitioners. Say plainly on the site how your service operates within that framework, and show who the practitioners are. Have your legal and clinical teams approve the wording.

Evidence of real use, stated carefully. Counts of consultations or states served are factual claims. Publish them only if you can substantiate them, with a date.

Third-party mentions that are earned. Independent coverage, partner pages and professional bodies that describe you accurately. Buying placements in "best apps" listicles is a poor idea: it invites unreliable sources and may breach advertising rules.

Guardrails for doctors and platforms

If your app lists doctors, the National Medical Commission's 2026 advertising guidelines apply to the practitioners, and they also address online healthcare platforms. Paragraph 9.4 requires platforms that list doctors to prohibit paid ranking and keep listings transparent; see the official notice and our summary. In practice:

• Do not market a doctor as "top" or "best" without a transparent, independent method.
• Do not publish patient testimonials as promotion.
• Do not manufacture reviews or ratings, or pay for them.
• Be careful with the claims that you "guarantee" anything about outcomes or response times.

An assistant that describes your platform as "the top-rated app" because a listicle said so is a different matter. You cannot control that, but you can avoid feeding the claim yourself.

Fix inaccurate answers without overreacting

Occasionally the audit shows an assistant saying something false about your service: a feature you do not have, a price you do not charge, or a safety claim you never made. Capture the exact text, the date and the engine. Correct the sources that likely fed it. Most engines provide a feedback route; use it with the screenshot. Do not mass-produce pages whose only purpose is to contradict a single answer.

For anything that touches clinical safety, such as an assistant implying that your app can handle emergencies, escalate to your clinical lead the same day.

Where to start

1. Write 40 prompts in patients' language across the eight groups above.
2. Run them on three engines, three times each, and record everything in the log.
3. Sort results into the pattern table and pick the top three causes.
4. Fix your own identity data first: site, app store, profiles.
5. Publish or improve the "what we are" page, with clinical and legal review.
6. Make a list of the sources the assistants cite, and approach them with accurate information.
7. Re-run after four weeks and compare, not against competitors' fortunes, but against your own baseline.

Our telemedicine platform marketing page shows how this audit fits into a wider growth plan, and the AI search optimisation service covers the ongoing work.