You are Doing Research Wrong
Learn how to automate hybrid research with GPT Researcher
Over the past few years, we’ve witnessed an explosion of new AI tools designed to disrupt research. Some, like ChatPDF and Consensus, focus on extracting insights from documents. Others, such as Perplexity, excel at scouring the web for information. But here’s the thing: none of these tools combine both web and local document search within a single contextual research pipeline.
This is why I’m excited to introduce the latest advancements of GPT Researcher — now able to conduct hybrid research on any given task and documents.
Web driven research often lacks specific context, risks information overload, and may include outdated or unreliable data. On the flip side, local driven research is limited to historical data and existing knowledge, potentially creating organizational echo chambers and missing out on crucial market trends or competitor moves. Both approaches, when used in isolation, can lead to incomplete or biased insights, hampering your ability to make fully informed decisions.
Today, we’re going to change the game. By the end of this guide, you’ll learn how to conduct hybrid research that combines the best of both worlds — web and local — enabling you to conduct more thorough, relevant, and insightful research.
