VMPL
New Delhi [India], September 7: For a business, being found online was once largely a contest for position. Secure a place on the first page of Google for an important search, attract the right visitor and convert that visibility into an enquiry or transaction.
Artificial intelligence is complicating that familiar journey.
People are still searching, but they are also asking. They are requesting comparisons, recommendations and explanations from AI systems that can assemble an answer before a user decides which website to visit.
For businesses, this creates an unusual moment. Traditional SEO remains commercially important, yet the definition of search is becoming considerably wider.
One Indian company studying that transition closely is ThatWare, founded by Tuhin Banik. What began with a strong foundation in advanced SEO has developed into a broader search-intelligence model connecting technical SEO and enterprise search with AI SEO, Answer Engine Optimization (AEO), Generative Engine Optimization (GEO), LLM SEO and AI visibility. ThatWare publicly describes its current methodology as combining technical search disciplines with machine interpretation and AI-driven discovery.
The distinction is important because the next contest for visibility may not always have ten ranked results.
Sometimes, it may have one answer.
A customer no longer follows one search journey
Consider a company looking for an enterprise search partner.
One executive might type “SEO company India” into Google.
Another might search for “enterprise SEO services.”
A third could ask an AI assistant to identify companies capable of handling a complex international website while also supporting visibility in AI-generated search.
All three people have commercial intent. Yet each can encounter a completely different discovery experience.
That is why the debate over whether AI will “replace SEO” may be asking the wrong question.
Businesses need conventional organic visibility today while preparing for discovery environments that are becoming more conversational, generative and entity-driven.
ThatWare's response has been to widen the SEO stack rather than abandon it. Its large-scale search offering, for example, combines conventional enterprise SEO requirements with AI SEO, AEO, GEO and LLM visibility across complex websites and markets.
The website is no longer the entire digital identity
This shift becomes clearer when looking at how machines understand companies.
A traditional SEO campaign may optimize a page around a commercially valuable subject. But an AI system asked to recommend companies may need to understand much more.
What does the company actually do?
Which services does it provide?
Where does it operate?
What expertise is it consistently associated with?
Do independent sources reinforce those associations?
Are its products, people and services clearly connected?
Does information remain consistent across its wider digital footprint?
These questions move optimization from webpages towards entities.
For Banik, this has become an important part of ThatWare's search-intelligence philosophy. The company's research increasingly looks at how search engines and AI systems interpret meaning, entities, context and relationships rather than relying on keywords alone.
That thinking is particularly relevant to enterprises, where one corporate identity may sit behind thousands of pages, multiple products, countries, executives and business units.
AEO begins with being useful
Among the new terms entering marketing discussions is Answer Engine Optimization.
AEO sounds highly technical, but its basic principle is surprisingly practical: information should be easy to understand and useful when somebody asks a question.
Businesses have spent years creating content around keywords. Answer-oriented discovery places greater emphasis on questions, context and clarity.
A software company, for example, should not merely say that its platform is “innovative.” It should clearly explain what problem the software solves, who it is designed for, how it differs, where it can be deployed and the circumstances in which it may or may not be appropriate.
That information is useful to customers.
It is also easier for machines to interpret.
This is why next-generation SEO services may increasingly combine search intent with answer intent.
GEO changes the competition again
Generative Engine Optimization introduces another consideration.
When an AI system constructs a response, businesses may no longer compete only for position one, two or three.
They may compete to become part of the response itself.
That does not mean companies can simply “optimize for ChatGPT” and guarantee inclusion. Generative systems differ, outputs change and no credible agency can promise permanent recommendations.
What organizations can strengthen is the information environment surrounding their brands.
Clear entities, useful content, technical accessibility, structured information, topical depth, credible third-party references and consistent descriptions all contribute to that environment.
ThatWare's published GEO approach similarly focuses on semantic clarity, entity authority and visibility within generative experiences rather than positioning GEO as a substitute for conventional SEO.
The result is a more mature way of looking at AI search optimization: not as a trick for influencing an AI system, but as the process of making a business easier for intelligent systems to understand and verify.
LLM SEO is creating a new visibility layer
Large language models add yet another dimension.
Someone researching a business can now ask several follow-up questions without conducting several separate searches.
“Who provides this?”
“Which companies operate internationally?”
“Compare these providers.”
“Which one works with enterprises?”
“What are their specializations?”
This conversational research process means businesses increasingly need a coherent identity across subjects rather than isolated pages targeting isolated keywords.
LLM SEO is emerging around this challenge.
ThatWare defines this area around making brands more understandable to large language models, while its wider AI-search work combines LLM SEO with AEO, GEO, technical SEO and entity optimization.
For an enterprise evaluating an AI SEO company, that breadth may eventually matter more than whether an agency has simply added an AI service page.
The next challenge is knowing whether any of it works
There is, however, an uncomfortable problem with AI search.
Businesses can easily measure a Google ranking.
Measuring whether a brand is becoming visible across AI-generated answers is harder.
This has pushed ThatWare's research into another direction: AI visibility measurement.
The underlying questions are commercially meaningful.
When users ask questions related to a company's products, is the brand present?
Is it mentioned alongside competitors?
Is its expertise represented accurately?
Is it cited?
Which topics generate visibility?
Where are competitors appearing instead?
For marketing teams accustomed to rankings and organic traffic, this introduces a new layer of competitive intelligence.
ThatWare has been developing frameworks around precisely this intersection of search visibility, entity understanding and AI discovery, reflecting its broader effort to treat search as an intelligence problem rather than merely a ranking exercise.
What businesses should expect from an SEO company now
For companies selecting an SEO agency in India or an international search partner, the changing environment may require a broader checklist.
Technical SEO still matters.
Enterprise scalability still matters.
Content, links, authority and conversions still matter.
But businesses may increasingly need to ask whether their SEO partner understands answer engines, generative search, large language models, structured information, semantic relationships, entity authority and AI visibility as well.
This is where ThatWare's positioning becomes noteworthy.
Rather than moving away from SEO, the company has expanded its interpretation of it. Its current search model connects established SEO disciplines with AI SEO, AEO, GEO, LLM visibility and entity-led optimization, including dedicated approaches for large-scale businesses.
It represents a broader shift that may eventually reshape the agency market itself.
The objective has not changed
Despite all the new terminology, businesses ultimately want something remarkably familiar.
They want to be discovered by the right customer at the right moment.
Yesterday, that largely meant appearing prominently in search results.
Tomorrow, it may also mean being understood when an AI system assembles a shortlist, being cited when it explains a subject, or being considered when it compares available solutions.
The strongest search strategies may therefore be those that refuse to choose between the old world and the new one.
ThatWare's direction offers one example of that philosophy: keep the technical and commercial foundations of SEO, then build AEO, GEO, LLM optimization, entity intelligence and AI visibility around them.
Search engines will continue evolving. AI interfaces will change. New platforms will emerge.
But for businesses, one principle is likely to survive all of them:
If customers are looking for what you provide, your business needs to be capable of being found, understood and considered.
(ADVERTORIAL DISCLAIMER: The above press release has been provided by VMPL. ANI will not be responsible in any way for the content of the same.)