The aroma of freshly brewed Turkish coffee still lingers in my memory, a familiar comfort as I reflect on a recent conversation that felt as layered and rich as the city I call home. Istanbul bridges two worlds and so does its AI scene, constantly seeking balance between tradition and relentless innovation. This time, my journey led me to a quiet cafe in Kadıköy, far from the usual tech hubs, to meet a man whose work is at the heart of one of the internet's most pressing debates: the future of web data in the age of Google's AI Overviews.
Kerem Güven, the founder of Scrape.do, a web scraping API service, has a story that begins not in a sterile server room, but amidst the vibrant chaos of Istanbul's Grand Bazaar. He told me his story over Turkish tea, a tale of early entrepreneurial spirit. "My family has always been in trade, in the bazaar," he explained, his eyes reflecting a deep understanding of commerce. "I learned about supply and demand, about finding what people need and providing it, very young." This foundational understanding, honed in the ancient marketplace, would later prove invaluable in the digital realm.
Kerem's "aha moment" came not from a sudden flash of genius, but from a persistent frustration. As a young developer, he saw businesses struggling to gather publicly available data from the web. Websites were complex, constantly changing, and often actively tried to block automated access. This wasn't about stealing information, he emphasized, but about legitimate data collection for market research, price comparison, and competitive analysis. "It was like trying to navigate the bazaar blindfolded," he chuckled. "You knew the goods were there, but you couldn't see them, couldn't touch them." The problem was clear: the open web, while theoretically accessible, was becoming increasingly difficult to programmatically interact with, especially for smaller businesses lacking dedicated engineering teams. This challenge has only intensified with the rise of large language models and Google's aggressive push into AI Overviews, which promise instant answers but potentially obscure the original sources of information.
Scrape.do was born from this necessity. Founded in 2018, the company provides a robust, scalable web scraping API that handles proxies, CAPTCHAs, and browser rendering, allowing users to extract data from virtually any website. Their technology acts as a bridge, much like Istanbul itself, connecting businesses to the vast ocean of public web data. "We handle the messy parts," Kerem explained, "so our clients can focus on what they do best: analyzing the data and making informed decisions." The core of their technology relies on a distributed network of residential proxies, sophisticated CAPTCHA-solving algorithms, and headless browser automation, all orchestrated to mimic human browsing behavior while remaining efficient and reliable. They essentially provide a clean, structured data stream from the chaotic, unstructured web.
The market opportunity for Scrape.do is substantial and growing, particularly as the digital landscape shifts. With Google's AI Overviews now providing synthesized answers directly in search results, many fear a reduction in traffic to original content creators and data providers. This creates a dual challenge and opportunity for companies like Scrape.do. On one hand, businesses may need to work harder to ensure their data is discoverable and integrated into these new AI paradigms. On the other, the demand for raw, verifiable data for training AI models, competitive intelligence, and market trend analysis is skyrocketing. Analysts estimate the global web scraping market to be valued at several billion dollars, with projections showing significant growth as data becomes an even more critical asset for AI development and business intelligence. Scrape.do, with its focus on reliability and ease of use, is well-positioned to capture a significant share of this expanding market.
"The internet is evolving," Kerem noted, "and with AI Overviews, Google is essentially becoming a content aggregator on an unprecedented scale. This doesn't mean the original sources disappear, but their visibility changes. Our role is to ensure that businesses can still access the foundational data that fuels their operations and innovations." This perspective is crucial. While some view AI Overviews as a threat to the open web, potentially reducing clicks to publishers, others see it as a transformation that necessitates new tools for data acquisition and analysis. Scrape.do provides those tools.
The competitive landscape is robust, featuring players like Bright Data, Oxylabs, and ScrapingBee. However, Scrape.do differentiates itself through its aggressive pricing, developer-friendly API, and a strong emphasis on customer support. "We pride ourselves on being accessible and responsive," Kerem stated. "Many of our competitors cater to enterprise clients with complex, expensive solutions. We want to empower everyone, from a small startup in Ankara to a global e-commerce giant, to access the data they need." This approach has resonated, allowing them to carve out a niche and attract a diverse client base, including e-commerce companies, financial institutions, and research firms. Their reported growth metrics, while not publicly disclosed in detail, suggest a strong upward trajectory, fueled by recurring revenue from their subscription-based model.
Funding for Scrape.do has been primarily bootstrapped, a testament to Kerem's pragmatic approach and the company's early profitability. This self-reliance has allowed them to maintain agility and focus on product development without external pressures. However, as they look to scale further and invest in more advanced AI-driven features, external investment may become a consideration. "We've proven our model," Kerem said, "and now we're looking at how to integrate more intelligence into our scraping, making it even smarter, more predictive." This includes exploring AI models to anticipate website changes and automatically adapt scraping logic, further reducing the burden on their clients.
What's next for Scrape.do? Kerem envisions a future where their service is not just a data extractor, but an intelligent data curator. They are exploring features that would allow users to not only scrape data but also to clean, structure, and even analyze it using integrated AI tools. Imagine a system that not only pulls product prices but also identifies pricing trends or competitor strategies automatically. This evolution aligns perfectly with the broader industry trend towards intelligent automation and data-driven decision-making. Their commitment to ethical scraping practices, respecting robots.txt protocols and avoiding excessive load on servers, also positions them as a responsible player in a sometimes controversial field.
As I left the cafe, the sounds of Istanbul's bustling streets seemed to echo Kerem's vision: a world where information, like the goods in the Grand Bazaar, is accessible to those who seek it, even as the marketplace itself transforms. At the crossroads of innovation, companies like Scrape.do are not just reacting to changes like Google's AI Overviews, they are building the essential infrastructure that will define how we interact with the open web in this new era. Their work ensures that the promise of the internet as a vast, accessible repository of knowledge remains, even as the gatekeepers evolve. The future of the open web, it seems, will depend on more than just search engines; it will depend on the ingenuity of those who build the bridges to its data. You can learn more about the evolving landscape of AI and its impact on the web by visiting TechCrunch's AI section or reading analyses from MIT Technology Review. The conversation around AI's impact on search and content is ongoing, as highlighted by discussions around Google's AI Overviews and their effect on curiosity [blocked].
