Google has owned online search for over two decades, but that dominance is finally being challenged. Search engines, chatbots, and AI answer engines are now competing to deliver better answers, with completely different approaches.

In 2026, traditional search tools fall into two categories: search engines that give you link lists, and chatbots that provide conversational responses. Even though some chatbots now have live search features, they typically don’t emphasize sources. AI answer engines try a third approach: delivering direct responses with prominent citations included.

With 10.5% of the AI chatbot market compared to ChatGPT’s 82.69%, Perplexity has become a real alternative to traditional search. This article answers three core questions: Who created Perplexity AI? When did it come out? And how does it challenge Google and ChatGPT dominance?

Who Created Perplexity AI?

Perplexity AI was created in 2022 by Aravind Srinivas, Denis Yarats, Johnny Ho, and Andy Konwinski. Their goal was to design an AI answer engine that could give clear and sourced responses instead of endless search links. What started as a small launch now competes directly with Google, Bing and ChatGPT.

The story behind who founded Perplexity AI is a mix of talent and timing. Srinivas had worked at OpenAI and Google Brain, Yarats came from Meta AI research, Ho had experience at Quora, and Konwinski was part of the Databricks founding team. They shared a simple idea: search should give real answers, not just blue links.

That vision caught on almost immediately. By the first months of 2023, Perplexity AI had already surpassed two million monthly active users, in a market where Google has held a virtual monopoly for decades. It was much larger than anyone expected, and it positioned Perplexity firmly on the map as a serious contender in the search industry.

What made it stand out was the mix of clear answers with visible sources, which felt more reliable than the noise of traditional search. Its reach expanded quickly: students leaned on it for solid references, professionals valued the speed and focus, and everyday users enjoyed a simpler way to explore their questions.

The quick rise across web and mobile highlighted a real demand for a search experience built on trust and ease of use.

The History Behind Perplexity AI: What Are Answer Engines & RAG?

Search engines still give you long lists of links that can take hours to verify. Chatbots offer a conversational approach, but they often invent information and don’t cite their sources. These mistakes, called AI hallucinations, are a known issue with many AI systems. It was in this context that Perplexity appeared, offering a different way to find information.

The story of Perplexity is built on solving both problems at once. Instead of forcing people to choose between messy results or answers they could not trust, it brings together two simple steps. First, it collects information from the web. Then it builds a response based on those sources and shows the citations. This design makes answers quicker to read and easier to trust.

The first beta was released in December 2022, followed by mobile apps in 2023. Over time, browsing features and design updates were added. By 2025, Perplexity had reached millions of users and gained recognition as one of the most important names in search.

ChatGPT have added live search features, but Perplexity makes citations the centerpiece, not an afterthought. The platform was designed specifically as an answer engine where sources are just as visible as the answer itself. This focus on transparency means fewer hallucinations and more trust.

People like Perplexity because it’s fast, clear, and open. You get a direct answer, you can see where it comes from, and read more if you want.

Who Owns Perplexity AI? 

Perplexity AI is privately owned. Ownership is split between the founders and a roster of high-profile investors, including venture capital firms like NEA and IVP, plus tech heavyweights like Jeff Bezos, Nvidia, and SoftBank. 

The company operates as a privately held company, meaning it is not publicly traded and doesn’t have a single controlling owner. The founders (Aravind Srinivas, Denis Yarats, Johnny Ho, and Andy Konwinski) still hold significant equity, but ownership is shared with institutional investors.

Perplexity raised its first funding round in 2023, securing around $25 million from firms like NEA and IVP. A year later, bigger names joined. Jeff Bezos, through his personal fund, took a slice, and Nvidia came on board too, seeing Perplexity as a good showcase for its chips.

In 2024, SoftBank stepped in with a large investment that pushed the company’s value into the billions. By 2025, reports suggested a valuation close to 14 billion dollars, with new funding in the works.

Is Perplexity AI biased? What Are The Risks and Errors?

Perplexity AI is not perfect, and it’s not free from bias or mistakes. Like any system that combines LLMs with web data, it can repeat the biases found in its sources, invent details, or overlook context. Although it reduces some of these issues by showing citations and filtering websites, the platform still carries risks such as hallucinations, uneven source quality, privacy concerns, and copyright disputes.

One of the main risks is AI bias. Because Perplexity draws on material already available online, it can amplify whatever viewpoints dominate those sources. Even with filters that block unreliable sites, biased perspectives still appear in answers..

Hallucinations are another weakness, though they happen less frequently in Perplexity than in traditional chatbots. This happens when the model fills in gaps with information that sounds convincing but is factually wrong. While citations help, a confident answer can still mislead if the source is inaccurate or if the model misreads the information. That’s why verifying critical details is important, especially when making decisions based on the output.

Source quality, privacy, and copyright round out the list of risks. A cited link does not always guarantee high credibility, and there have been controversies over the way Perplexity collects and uses content from the web.

Privacy advocates point out that large-scale crawling can capture information that was not meant to be redistributed, while publishers question whether the reuse of their work is fair.

Conclusion

In 2025, search changed more than it had in the last two decades. For the first time, Google faces real competition from AI-powered answer engines. Even Google has responded, launching AI Overviews and AI Mode as users move away from link lists. Perplexity will likely keep improving how it displays sources, making citations clearer and verification faster. Expect real-time data integration, industry-specific filtering like academic papers, news outlets, or government sources, and user controls that let you prioritize certain publishers over others.

The era of clicking through ten blue links is over. Users now expect direct answers with verifiable sources, but they also want privacy. Future systems will probably let you search across your own Google Drive, Notion workspace, or company databases without exposing sensitive information to public models. For businesses, this means audit trails that show exactly which sources informed each answer and compliance tools that prevent unauthorized data use.

When ChatGPT launched in 2022, it proved conversational AI could go mainstream, reaching 100 million users in two months. Perplexity took a different bet: slower initial growth but higher trust through mandatory citations. Both approaches work for different needs. ChatGPT excels at brainstorming, drafting, and creative problem-solving where exact accuracy matters less.

Perplexity wins for research, fact-checking, and decisions where wrong information has consequences. The future isn’t one replacing the other; it’s knowing which tool fits the task.

Origianl Creator: Paulo Palma
Original Link: https://justainews.com/blog/who-created-perplexity-ai-and-when-did-it-come-out/
Originally Posted: Sat, 11 Oct 2025 10:39:41 +0000