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Which AI search monitoring platform an Indian agency should buy for its clients

Seven requirements that only matter when you are reselling the reading, and the two that eliminate most of the category immediately.

Published by AI Knows Us · Updated 22 October 2026

An Indian agency buying AI search monitoring for client work has a different shopping list from a brand buying it for itself. You need per client separation, enough question capacity to cover several accounts, a report a client will accept, and a cost base that leaves you a margin at Indian retainer levels. Most of the category is built for the single brand buyer. Here is what to require.

The two requirements that eliminate most options

  1. Several businesses on one subscription, properly separated. If the product is built for one brand, running five clients means five subscriptions, and your margin disappears before you have done any work. Ask directly how many separate businesses a single account covers.
  2. Enough tracked questions to cover a portfolio. A plan watching 20 questions is one client's worth. Across five clients you need five times the capacity, and question capacity is the main cost driver in every product in this category.

Ask both questions in the first email. They will shorten the list faster than any feature comparison.

The other five requirements

  • A report you can put in front of a client unedited. If you have to rebuild the output in a deck every month, the tool has added work rather than removed it.
  • Per engine reporting. A blended score across engines is not a number, and the reason is measured below.
  • Citation and naming as separate columns. Being used as a source and being recommended are different results that fail for different reasons. A product that merges them will make your client reports wrong in the most expensive available way.
  • The market fixed in the prompt. If the product sets the country with an API parameter, it is not measuring India. The gl, hl, location and country parameters are accepted, return 200 and answer from somewhere else.
  • An exportable record you keep. When a client leaves, the history should be portable. When a client arrives, you want to show them a baseline from day one.

Why per engine reporting is not a preference

On 22 October 2026 we put a 198 question set of Indian buying questions to ChatGPT and Gemini, with the market written into the prompt, and took 64 blind readings, 32 per engine. ChatGPT carried 2,929 of the 3,031 citation URLs in that set. Gemini carried 102, and 3 of its 32 readings carried none at all.

Any product averaging those two into one score is averaging two different instruments. For an agency this is not an academic point: it is the difference between telling a client their sources improved and being able to show which engine moved. Ask any vendor to show you a client report with the engines on separate lines before you buy.

What the Indian market looks like in these readings, which is your sales argument

  • 37 of the 64 readings named at least one supplier and 27 named nobody at all. For a client in a category where the answers name nobody, you are selling a first mover position rather than a catch up.
  • Indian agencies are named unprompted. Schbang appeared in 12 readings, Infidigit in 7, PageTraffic in 7, Techmagnate in 7, Social Beat in 7 and WATConsult in 7, in questions that named no firm. If your own agency is not in that set, that is a pitch for your own marketing as well as your clients'.
  • The source list is wide. 1,145 distinct hosts across the set, 905 cited exactly once. There is no gatekeeper list to buy onto, which is good news for a competent publisher.

One hygiene note that matters when you are presenting source data to a client. The India set contains ccn.web.tr, a host of the form developers-google-com followed by a random string, and a developers.google.cn mirror. Those are proxies and mirrors rather than publishers. A report that lists them as citation sources has not been read by a person, and a client who notices will be right to ask what else was not checked.

What our own agency tier costs, with the date

We quote ourselves and not competitors, deliberately, because an undated competitor price in this category becomes a figure somebody argues with. Read from aiknowsus.com on 22 October 2026, the India column shows the Agency tier at Rs 70,999 a month with 80 buyer questions watched, 12,300 credits a month and all five engines read. That credit pool is more than twice the next tier up on fewer questions, which is what a plan serving several client businesses looks like rather than a single brand.

For comparison within our own ladder, Growth is Rs 11,799 a month with 100 questions and five engines, which is the right shape for one business rather than a portfolio. And the Rs 4,999 tier reads zero engines, so it is not an AI visibility plan at all and should not be resold as one.

What Indian agencies ask when buying this for clients

Can we white label the report? Ask the vendor explicitly and get the answer in writing, because it varies and it changes what you can charge. If you cannot, decide whether your clients mind being shown the source.

What do we charge on top? Price the interpretation and the work, not the subscription. Clients will discover the subscription price and marking it up is a conversation nobody enjoys.

How many questions per client? Enough to cover the ways their buyers actually ask, which is usually between ten and fifty for a single market client. Write the list with the client; it is the asset they keep.

Should we offer this as a standalone service? It works best attached to the publishing work, because a reading with nobody acting on it stops being bought in month four. Sell the loop, not the dashboard.

What about clients outside India? Check which price column applies to them, because this category prices by market and your client's country may not be yours. Quote one market's price per conversation.

What we would want you to resell, and what we would not

The part worth reselling is the loop: a client's own question set, read every month across ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews, with citation and naming kept separate, each engine on its own line, and any reading where the question named the client excluded as a ceiling measurement. That is what AI Knows Us produces, at the India prices above read from aiknowsus.com on 22 October 2026. The part not worth reselling is a dashboard with no decision attached, which is what clients cancel first.

For what the engines currently name in this category in India, which is useful background before you pitch, see our page on the GEO agencies the engines name in India.

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