Latest news with #AndrewYan


Mint
a day ago
- Business
- Mint
The companies betting they can profit from Google search's demise
A new crop of startups are betting on the rapid demise of traditional Google search. At least a dozen new companies are pouring millions of dollars into software meant to help brands prepare for a world in which customers no longer browse the web and instead rely on ChatGPT, Perplexity and other artificial-intelligence chatbots to do it for them. The startups are developing tools to help businesses understand how AI chatbots gather information and learn how to steer them toward brands so that they appear in AI searches. Call it the search-engine optimization of the next chapter of the internet. 'Companies have been spending the last 10 or 20 years optimizing their website for the '10 blue links' version of Google," said Andrew Yan, co-founder of Athena, one of the startups. 'That version of Google is changing very fast, and it is changing forever." Companies large and small are scrambling to figure out how generative AI tools treat their online content—a boon to this new crop of startups, which say they are adding new customers at a clip. The customer interest is an early sign of how AI is transforming search, and how companies are trying to get ahead of the changes. Yan left Google's search team earlier this year when he decided traditional search wasn't the future. Athena launched last month with $2.2 million in funding from startup accelerator Y Combinator and other venture firms. Athena's software looks under the hood of different AI models to determine how each of them finds brand-related information. The software can track differences in the way the models talk about a given brand and recommend ways to optimize web content for AI. Yan said the company now has more than 100 customers around the world, including the online-invitation firm Paperless Post. Google executives and analysts don't expect traditional search to disappear. The company, which handles as much as 90% of the world's online searches, has been working to incorporate AI features into its flagship search engine and anticipates people will continue to use it alongside other tools such as Gemini, its AI model and chatbot. Yet the company, a unit of Alphabet, has been under pressure to compete with OpenAI's ChatGPT and other AI upstarts that threaten its core business. It risks losing traffic and advertising revenue if users shift to AI-driven alternatives. Chief Executive Sundar Pichai has said that AI Overviews, a feature that summarizes search results at the top of the page, has grown significantly in usage since the company launched it in 2024. Google earlier this year began rolling out AI Mode, which responds to user queries in a chatbot-style conversation with far fewer links than a traditional search. Compared with traditional search, chatbot queries are often longer and more complicated, requiring chatbots to draw information from multiple sources at once and aggregate it for the user. AI models search in a number of ways: One platform might pull information from a company website, while another might rely more heavily on third-party content such as review sites. Of the startups helping companies navigate that complexity, Profound has raised more than $20 million from venture-capital firms including Kleiner Perkins and Khosla Ventures. The company is building its platform to monitor and analyze the many inputs that influence how AI chatbots relay brand-related information to users. Since launching last year, Profound has amassed dozens of large companies as customers, including fintech company Chime, the company said. 'We see a future of a zero-click internet where consumers only interact with interfaces like ChatGPT, and agents or bots will become the primary visitors to websites," said co-founder James Cadwallader. Venture-capital fund Saga Ventures was one of the first investors in Profound. Saga co-founder Max Altman, whose brother is OpenAI CEO Sam Altman, said interest in the startup's platform has exceeded his expectations. 'Just showing how brands are doing is extremely valuable for marketers, even more than we thought," he said. 'They're really flying completely blind." Saga estimates that Profound's competitors have together raised about $21 million, though some haven't disclosed funding. The value of such companies is still infinitesimal compared with that of the search-engine optimization industry, which helps brands appear in traditional searches and was estimated at roughly $90 billion last year. SEO consultant Cyrus Shepard said he did almost no work on AI visibility at the start of the year, but now it accounts for 10% to 15% of his time. By the end of the year, he expects it might account for as much as half. He has been experimenting with startup platforms promising AI search insights, but hasn't yet determined whether they will offer helpful advice on how to become more visible in AI searches, particularly as the models continue to change. 'I would classify them all as in beta," he said. Clerk, a company selling technology for software developers, has been working with startup Scrunch AI to analyze AI search traffic. Alex Rapp, Clerk's head of growth marketing, said that between January and June, the company saw a 9% increase in sign-ups for its platform coming from AI searches. Scrunch this year raised $4 million. It has more than 25 other customers and is working on a feature to help companies tailor the content, format and context of their websites for consumption by AI bots. 'Your website doesn't need to go away," co-founder Chris Andrew said. 'But 90% of its human traffic will." Write to Katherine Blunt at


Forbes
17-06-2025
- Business
- Forbes
The Wild West Of AI Search And How One Startup Is Helping Brands Navigate The Post-Google Era
Athena founders The death of Google search as we know it may be greatly exaggerated, but the writing is on the wall. As millions of users increasingly turn to ChatGPT and other AI assistants for everything from restaurant recommendations to product research, a fundamental shift is underway in how consumers discover and evaluate brands. For companies that have spent decades mastering the art of Google SEO, this transition represents both an existential threat and an unprecedented opportunity. Enter Athena, a five-person startup that claims to have cracked the code on what founder and CEO Andrew Yan calls "Gen AI Engine Optimization" – essentially SEO for the age of artificial intelligence. Athena has raised 2.2 million dollars from Y Combinator, FCVC, Red Bike Capital, Amino Capital, and various search and SEO industry angels. The company currently serves over 90 customers across retail, e-commerce, and B2B SaaS sectors has emerged from stealth just months ago. Yan's journey to founding Athena began during his tenure on Google's search information acquisition team, where he witnessed firsthand the tectonic shifts reshaping how people find information. "I realized that search and shopping and how people are discovering products is about to massively change and do this 180-degree turn," he explains. "People are using ChatGPT like a personal assistant, and they're trusting it more than Google – it's becoming more persuasive, and people are relying on it even more to make decisions." This insight led Yan to a sobering realization: hundreds of billions of dollars in brand value that companies have built through traditional Google advertising and SEO could be at risk. "It's no longer just informational – it's actually going down into the decision-making layer," he says of AI-powered search. "Right now, it's kind of this wild west where there are hundreds of billions of brand dollars worth of brand value at stake." What sets Athena apart in this emerging market isn't just its technology, but its execution speed. While established SEO platforms like Ahrefs and SEMrush attempt to adapt their traditional tools to the AI era, and newer competitors like Orderly race to build similar solutions, Athena has focused on delivering what Yan calls "the fastest time to value" – customers can sign up and receive actionable insights within minutes. The company's approach centers on four key pillars: Gen AI monitoring, Gen AI insights, actionable recommendations, and attribution of impact. This last component may be the most crucial differentiator. "We had a customer who used our tool to help them beat out much bigger competitors who are 20 to 30 times as big," Andrew notes. "Using Athena, they're able to beat them on Gen AI search, which is indicative of this wild west – how the right company with the right tool in this space can actually have an outsized presence." Athena platfrom Perhaps more intriguing than Athena's technology is its business model innovation. Rather than following the traditional SaaS playbook of flat monthly fees, the company has adopted a credit-based system that scales with customer success. Users pay a platform fee and receive an initial bucket of credits, but can purchase additional credits as they see value and want to expand their AI search optimization efforts. "This allows us to align our incentives with our customers," Yan explains. "We win when our customers win and they see value in the data and want to buy more credits." The model also provides flexibility – companies can choose to track many prompts with shallow data or focus deeply on fewer search queries, depending on their needs. This approach reflects a broader trend in AI-powered software toward outcome-based pricing models, though it requires educating both customers and investors accustomed to predictable monthly recurring revenue. "Obviously, investors are used to the traditional monthly SaaS fee," Andrew acknowledges. "But when I speak to them about the credit-based system, they get that we want to be able to align our incentives with our customers." Athena's rapid growth exemplifies what Yan sees as a fundamental shift in startup dynamics. The company has achieved its traction with just five employees, all based in San Francisco, leveraging AI tools like Cursor, Windsurf, and Claude to punch above their weight class. "We had our first line of code in February, and now we're almost 100 customers, with revenue growing, doubling consistently month-on-month," he says. "This wouldn't be possible without these tools." This efficiency reflects what some observers call "vibe coding" – the ability of small teams to achieve outsized impact through AI-powered development tools. Andrew frames it differently: "AI is giving people leverage. Whereas before it might take three software engineers, now you only need one, and if they're using the right tools the right way, then a smaller company can compete." The implications extend beyond Athena's own operations. Y Combinator companies, Andrew suggests, are growing faster than ever before, with smaller team sizes achieving rapid scaling that would have required much larger organizations in the pre-AI era. For all the talk of AI transformation, Athena's value proposition comes down to concrete, actionable insights. Take a Fortune 500 company like Adobe (used here as a hypothetical example): the company might discover through Athena's analysis that certain content assets are performing poorly in AI search results, presenting an opportunity to refresh existing content rather than creating new material from scratch. "Here are your top-performing Gen AI content pieces, and here are your worst-performing ones," Yan explains the typical customer interaction. "The worst-performing ones are where you have the most opportunity to refresh, improve, and increase the performance of these content pieces for Gen AI search." This granular approach to optimization reflects the challenge facing brands in the AI era: unlike traditional Google search, where ranking factors are well-understood (if constantly evolving), AI search optimization requires entirely new strategies and metrics. While Athena's growth metrics are impressive – the company reports mid-six-figure revenue and expects to reach several million dollars in annual recurring revenue by year-end – the broader AI software market faces a critical challenge: customer loyalty. Unlike traditional SaaS products that become deeply embedded in business processes, many AI tools remain experimental, leading to higher churn rates and making it harder to build sustainable businesses. This dynamic has raised the bar for AI startups seeking venture capital. Where once a YC demo day company might attract Sand Hill Road attention with modest traction, observers now suggest AI companies need closer to one million dollars in annual recurring revenue to be taken seriously by top-tier VCs. Yan seems confident Athena can clear this hurdle, but the broader question remains: as AI search continues to evolve rapidly, will specialized optimization tools like Athena become essential business infrastructure, or will they remain nice-to-have experiments that companies abandon when budgets tighten? Whether Athena succeeds or fails, the company represents a bet on an inevitable transition. As AI assistants become more sophisticated and users grow more comfortable relying on them for high-stakes decisions, the ability to influence these systems will become increasingly valuable. The question isn't whether this transformation will happen – it's who will emerge as the winners when the dust settles. For brands, the choice is becoming clear: adapt to the new reality of AI-mediated discovery, or risk becoming invisible to a generation of consumers who see ChatGPT, not Google, as their primary research tool. Companies like Athena are betting that this transition creates a multi-billion-dollar market opportunity. Time will tell if they're right – but in the wild west of AI search, the early movers may have the best chance of staking their claim to valuable territory.