Exclusive | From Search to Answers: Why brands must optimize for the AI-first era

For years, marketers have built their digital playbooks around search, social, mobile, performance, creators and content. But a new discovery shift is taking shape, one that is already changing how consumers find brands, compare products and make decisions as they move from search links to AI-generated answers.

Seeking to help brands navigate this shift is Kirthiga Reddy’s OptimizeGEO.AI, an end-to-end platform designed to help brands understand where they appear in AI-generated responses, why they appear and what they must do next. Having witnessed some of the biggest technology and consumer shifts from close quarters, Reddy sees this as another defining moment for marketing.

She says, “Having seen the last shift to social and mobile from the front seat, and really co-created the future of marketing with leading marketers, it is such a joy and a thrill to be doing it again in this AI-first era.”

Speaking about the company, Reddy shares that the firm is focused on what is now being described as generative engine optimization, or GEO — the discipline of helping brands become visible, accurate, trusted and recommended inside AI-generated answers.

Why this moment matters

The shift is significant because consumers are no longer only typing keywords into a search engine and choosing from a list of links. They are increasingly asking AI assistants more detailed, context-rich questions and receiving answers that can influence awareness, consideration, evaluation and purchase decisions in one interaction.

“We are seeing this mega shift where people are no longer going to traditional search for finding anything from skincare advice to which enterprise solution to buy,” she says. “They’re going to ChatGPT, Perplexity, Anthropic and the like.”

“It’s no longer keywords, right? They’re asking questions with a lot of context about a specific scenario,” Reddy says. “We have the whole rise of zero-click buyer behavior, where you start from a question, and you go from awareness to consideration to evaluation to a decision, all in one interaction.”

For brands, this creates a simple but serious question: are they present in those answers?

“Where consumers go, marketers need to go,” Reddy says. “If you’re not visible in those answers, you’re essentially forgotten by the modern consumer.”

That is the core problem OptimizeGEO.AI is trying to solve.

Beyond visibility: Understanding the ‘Why’

Reddy describes OptimizeGEO.AI as an end-to-end platform that begins with diagnosis and moves all the way to recommendations and execution. The first layer helps brands understand what users are actually asking in their category. The platform then shows where the brand stands today in AI-generated answers, how it compares with competitors, and what it needs to do to improve visibility.

“It’s an end-to-end platform that goes from the diagnostic side, where we help you analyze what users are asking for in your particular category, to then giving you a dashboard of where you stand today,” she says.

But Reddy is clear that OptimizeGEO.AI does not want to leave marketers staring at data without a way forward.

“We don’t just leave people with a bunch of data,” she says. “We actually have a whole bunch of agents that help you. So we have a recommendations agent that’s constantly watching and saying, what is it that you need to do? Whether it is your content strategy, whether it’s your partnership strategy, whether it’s your media strategy.”

The growth trajectory

The platform was launched around late December 2025 after a beta phase. Reddy says it was built “with the Fortune 1000, for the Fortune 1000,” and that the company went from zero to a million dollars in ARR in a few months.

“We went from zero to a million dollars in ARR in a few months, and we’re tracking to 10x that,” she says. “Startups are about adding a zero.”

The ambition is larger than GEO as a narrow marketing acronym. Reddy sees generative engine optimization as the entry point to an autonomous growth engine for the AI-first era.

“The whole generative engine optimization space, search engine moving to generative engine, is only an entry point,” she says. “But how do you use that to create an autonomous growth engine in the AI-first era? That is our goal.”

The persona-driven approach

Reddy also shareshow the platform can track prompts in specific categories. In a baby-care example, the question was not a traditional keyword string. It was a real-world AI-style query: “pediatrician-recommended baby wash for sensitive skin in India.”

That distinction matters. “Right here, you can see how different this is from a keyword search,” Reddy says. “There’s a lot of context that you’re getting.”

“The first part is us helping you understand what people are asking for by different personas,” Reddy says. “We are one of the only platforms that gives you a persona-driven approach.”

“The consumer is an audience. The dealer is an audience. The AI visibility score for one versus the other might be different,” she says.

The reality check: Hidden vulnerabilities

The platform then runs actual prompts across AI platforms and tells brands how they are appearing compared with others. It measures visibility score, share of voice, frequency of appearance and prompt-level performance.

This prompt-level view is important because a strong aggregate score can hide significant weaknesses.

“Even though your overall visibility score might be really high, on average, we see about 40% of the questions that brands identify as really important for them, they are at 0% visibility,” Reddy says.

“Now we are telling you why the LLMs gave the answers that they did,” she says. “Why was Johnson’s Baby number 11 and not number one?”

AI as a Mirror of the Web

The platform can show the sources that AI systems are drawing from, including YouTube pages, pharmacy sites, Google results, Instagram, Amazon and other third-party sources. For marketers, this can influence content strategy, media strategy, partnership strategy, PR strategy and even customer education.

“We give you a lot of information that helps you influence your strategy, media strategy and the like,” Reddy says.

Reddy makes an important point here. Brands often think they are optimizing for AI search. But AI search is also a mirror of what already exists across the web.

“While people think that their optimization is for AI search, AI search is simply telling you the aggregate of what is out there on the web,” she says.

Business signals, not just SEO metrics

Reddy shared examples where brands had strong overall visibility but were missing from important answer areas. A Fortune 1000 baby-care brand was not appearing strongly around safety-related concerns.

A personal care device brand was not appearing around post-device care. An enterprise solution had visibility, but was weak on questions around post-purchase customer service.

These are not narrow SEO issues. They are business signals. “If you’re investing a dollar in marketing, in your content, regardless of AI search, content, media — this is information that you really need to have,” Reddy says. “It will help you drive the ROI of all your other marketing mix investments.”

From Diagnosis to Execution

OptimizeGEO.AI‘s next layer is execution. The platform has an Action Center and a recommendations agent that tells brands what they need to do to fix gaps. It can point to content, partnerships, media or other interventions. Reddy also says the company is building agents that can help create and publish content based on actual LLM-derived topics and visibility gaps.

“It is not random topics,” she says. “It is based on the topics that are coming up in LLMs, based on how you appear.”

The company is also building what Reddy calls an autonomous growth engine, which can integrate with a CMS system, auto-publish content, monitor response and learn from performance.

“This is the area that we’re building out — all of our agentic interfaces,” she says.

Why automation matters

For marketing teams, this matters because GEO can quickly become a workload-heavy discipline. Teams have to understand changing prompts, multiple AI platforms, citation sources, answer shifts, visibility fluctuations and action priorities. Reddy says most teams she speaks with, whether at large enterprises, midsize companies or startups, are already stretched.

“Every team that we talk to, whether it’s a Fortune 50, or a midsize company, or a startup, everybody is short-staffed and doesn’t have bandwidth. And this is a brand-new field as well,” she says.

That is why OptimizeGEO.AI wants its agents to do the heavy lifting.

“We really pride ourselves on being the platform where our platform and our agents help you do the heavy lifting, so you don’t have to,” Reddy says.

The trust imperative in regulated categories

Regulated and high-trust categories are another important area. In health, fintech and other sectors, visibility alone is not enough. Accuracy matters. Incorrect AI answers can have serious consequences. Reddy says OptimizeGEO.AI has built an accuracy agent, or trust agent, for such use cases.

“One of the very unique capabilities that we have in our product is something that we call an accuracy agent or a trust agent,” she says. “It becomes very important information because these can have huge consequences.”

The trust agent can assess whether AI platforms are answering sensitive or regulated questions accurately. Reddy says fintech and healthtech clients are already heavily dependent on these accuracy score features.

“We do have fintech clients. We have healthtech clients that are heavily dependent on our accuracy score features,” she says.

The publisher opportunity

For publishers too, the shift could be important. If AI answers depend on credible citations, publishers that are frequently cited may become more influential in the AI discovery ecosystem. Reddy says OptimizeGEO.AI is already speaking with publishers on how often they are cited and how they can become stronger sources of citations.

“Where are the citations coming up? How often are you cited? How can you become a greater source of citations? All of that is possible,” she says.

Category adoption across industries

The company is also seeing strong category interest. Reddy says CPG, technology, telecom, fintech and e-commerce, which led the earlier social and mobile transition, are also leaning into AI visibility. But the need is not limited to large consumer categories.

“We had very briefly released our self-serve module too, and we saw local dentists signing up for it,” she says. “Because, again, if someone looks for the best place to go for a crown implant, where do I come up?”

For now, OptimizeGEO.AI is focused on large and midsize enterprises, but the self-serve interest points to how widely this shift could travel.

“Today, we are quite focused on the large and midsize enterprise, but we will release our self-serve module at some point,” Reddy says.

India’s role in the AI discovery story

India is also part of the company’s growth story. Reddy says OptimizeGEO.AI is seeing adoption across the spectrum, from large enterprises and MNCs to Indian companies and startups.

“In India, we have brands from the Fortune 50, Fortune 1000 in India, to leading MNCs, to the upcoming startups, across the spectrum,” she says.

“From the banking side, whether it’s an ICICI Bank, to the CPGs, to all of the usual MNC suspects that you can think about, to Indian companies like Cholamandalam — you are really seeing adoption across the board,” she says.

The IPL Lesson: Sponsorship doesn’t guarantee AI visibility

Sports and live media moments are another part of the OptimizeGEO.AI thesis. The company studied IPL and AI visibility, examining how brands surfaced in AI conversations and how that interacted with sponsorship presence.

Reddy says the IPL work showed that media presence alone does not automatically translate into AI visibility.

“Kia and Mahindra were both IPL sponsors, both in the same category,” she says. “However, one of them was far more present versus the other in AI visibility.”

“You could be spending the same amount from your media strategy, but unless you also have a concentrated AI visibility strategy, you’re going to have very inconsistent results,” Reddy says.

She also points to the importance of being present across platforms. During the IPL period, a Google update affected AI visibility numbers. Brands that had strategies across different platforms were more resilient than those optimizing for only one.

“People who had a strategy across the different platforms versus just optimizing for one saw a smaller overall hit compared to people who were just optimizing for one platform,” she says.

Leapfrog or lose your lead

Reddy’s advice to marketers is direct. Do not wait for the shift to become obvious. And do not assume leadership positions are safe.

“If you are in the number two or number three spot, this is your opportunity to leapfrog,” she says. “We know market share is won and lost at times of transition.”

And for market leaders, her message is even sharper. “If you’re number one, please act like the number two or the number three, because otherwise you’re going to lose your spot.”