SerpApi, based in the U.S., delivers instant organized data from public search results; it claims free access to this information which plays a key role in building AI tools. With worldwide interest growing in dependable data use, the firm points out that clear, checkable sources can boost trust in automated content systems.
SerpApi, founded in 2017 and headquartered in Austin, Texas, provides developers, businesses, and researchers with a unified API that delivers structured results from major search engines including Google, Bing, Yahoo, Baidu, and Yandex. The company processes millions of API requests daily and is used across industries focused on automation, analytics, and AI-driven research. SerpApi said its mission is to ensure reliable, real-time access to public information so that AI systems can be built on transparent, reproducible data.
Rising Need for Transparent Data in AI Systems
As organizations adopt generative AI tools at scale, industry analysts highlight the importance of traceable and verifiable training data; for example, the global AI infrastructure market is expected to grow from about $35 billion in 2023 to $223 billion by 2030, citing rapid demand for real-time, public data-feeds.
Publicly accessible search-engine results are among the largest sources of real-time signals about online content and global information flows, a trend that mirrors the surge in AI-infrastructure investment globally. SerpApi said structured access to this type of data enables developers to build AI systems that reflect up-to-date public knowledge while maintaining visibility into the source of the information used.
“Our work is guided by a simple principle: public search data should be accessible,” said Julien Khaleghy, founder and CEO of SerpApi. According to SerpApi, modern language models are effective at synthesis but do not inherently provide fresh, verifiable information, which is why structured access to public data is increasingly important for transparency in AI systems.
Data Infrastructure Behind AI and Search-Powered Tools
SerpApi acts as a data infrastructure platform for a broad range of applications, from business intelligence systems and automation workflows to AI agents, search-powered assistants, and research tools. By delivering real-time structured results in JSON format, the API supports use cases where accuracy, speed, and reproducibility of data collection are essential.
The company noted that developers building LLM applications, RAG systems, and research agents rely on SerpApi to access real-time, verifiable search results. SerpApi’s support for more than 50 specialized APIs and its global coverage across localized markets allow developers to gather public information at scale without maintaining complex scraping infrastructure.
According to SerpApi’s published benchmark data, the company reports an average API response time of approximately 0.73 seconds. SerpApi also provides a 99.95% service-level agreement (SLA) for all plans, which includes a 100% penalty clause and service credits of up to the full monthly plan price if uptime falls below the guaranteed threshold. The company said this level of reliability is important for AI applications that require constant and predictable access to external data sources.
Ethical Access to Public Information
SerpApi emphasized that its data pipeline is designed for public information only. The company said it adheres to industry practices that respect public data boundaries, does not store personal information beyond what is technically required for processing, and implements encryption standards for secure data handling.
Its approach aligns with broader discussions in the AI community about ensuring that training datasets and real-time inputs reflect sources that are publicly accessible and that the process of collecting them is transparent and auditable. SerpApi said it aims to support developers, researchers, and organizations who prioritize ethical data workflows and require consistent visibility into the origins of information used in AI models.
Growing Demand From AI Builders and Research Communities
The rise of generative AI has created new demand for structured, query-ready data. SerpApi said its customers use the API to automate information-gathering tasks, build market intelligence dashboards, power academic studies, and integrate real-time search results into machine-learning pipelines. Developers building LLM-powered tools have increasingly adopted structured search data to improve accuracy in question-answering, fact retrieval, and analysis tasks.
Use cases outlined by the company include AI agents that require up-to-date public information, search-driven chatbots that respond with verifiable data, and data-processing systems that rely on high-frequency inputs from global search engines. SerpApi’s documentation highlights examples across marketing analytics, academic research, automation tools, and AI development workflows.
Continuous Product Development
Over the past year, SerpApi has expanded support for additional search endpoints, improved parsing accuracy, and added enhancements to its data extraction and regional targeting capabilities. The company continues to update its APIs to maintain compatibility with evolving search engine structures and to support developers building real-time intelligence solutions.
SerpApi provides more than 50 specialized APIs, including Google Search, Google Images, Google News, Bing Search, Baidu, and others, allowing developers to integrate structured public information into dashboards, reporting tools, AI models, and automation systems.
About SerpApi
SerpApi provides real-time structured access to public search engine results. Founded in 2017 by Julien Khaleghy, the company powers developers, researchers, and businesses with transparent, ethical data-collection tools that support innovation in AI, automation, and analytics. For more information, visit serpapi.com.
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