Luke Kim is the founder and CEO of Liner, a cutting-edge artificial intelligence research tool designed to simplify and enhance the research process, helping users complete tasks 5.5x faster. As an AI search engine, Liner provides filtered search results for precise information and automatically generates citations in a variety of formats, making it a valuable resource for researchers, students, and professionals.
Can you tell us about your background and what inspired you to pursue entrepreneurship, specifically in the field of artificial intelligence and technology?
My entrepreneurial journey began with a desire to solve real-world problems through technology. As an undergraduate, I was struck by how challenging it is to navigate and trust the vast amounts of online information. I was motivated to create a tool that would streamline the process and help students identify sources. What started as a highlighting tool that sifted through available information evolved over time into what Liner is today: an AI-powered search that delivers only the most reliable results. I am attracted to artificial intelligence because of its potential to change the way we process and interact with data. The opportunity to create meaningful solutions for students (like my younger self) continues to inspire me.
How did your experience building browser extensions in college shape the vision for Liner?
The Liner Highlighter browser extension was my first real attempt at solving the information overload problem. It shows me how much people value tools that make it easier to find and organize key information. I’ve learned that streamlining even one step in your workflow can have a big impact, whether it’s highlighting important points or showing relevant sources. This project shapes Liner’s commitment to creating seamless experiences for users and helping students and researchers cut through excess noise on the Internet.
What was the original vision behind Liner? How has it evolved since its inception?
Liner started out as a simple tool that helped users highlight and save key parts of online content. The goal is to make it easier for users to focus on the most relevant information without becoming overwhelmed. Over time, we realized that users needed more than just a way to collect and categorize information, they needed better ways to find information and discern its reliability. This realization led Liner to transform into an artificial intelligence search engine.
What were the main challenges you faced in transforming Liner from a highlighting tool into an AI-powered search engine?
One of the most significant challenges is ensuring that our AI can consistently deliver reliable and accurate results. Academic research requires a high level of trust, and meeting these expectations is critical. Another challenge is integrating years of user-highlighted data into the AI’s training process while keeping the platform intuitive. Striking the right balance between technological innovation and seamless user experience is critical, but also incredibly rewarding.
By building Liner’s definition of “agent” from the ground up, we were able to create a strong and stable framework for understanding what agency really means. We then implemented a search agent that prioritized reliability and trustworthiness. Given that our target audience represents the pinnacle of credibility-focused expectations, we needed a unique solution capable of solving the most complex problems. Our strength lies in leveraging our proprietary data sets, technical insights gained during the agent definition process, and our implementation expertise. Together, these elements are our most powerful tools for success.
Can you elaborate on how the integration of user-focused data improves the accuracy and reliability of Liner’s AI search results?
User-highlighted data acts as a valuable layer of quality control, helping our LLMs discern content that other users find important and trustworthy. By leveraging this curated data, we are able to prioritize relevant and trustworthy information in our search results. This approach ensures users receive precise and actionable insights while avoiding irrelevant or low-quality content.
How does Liner differentiate itself from other AI search tools like ChatGPT or Perplexity?
Liner stands out for prioritizing reliability and transparency. Each search result includes citations, and users can filter out less reliable sources to ensure accuracy. As an added measure, students can take the source and view the original quoted text on screen. Unlike tools designed for casual inquiry, Liner is built for students, academics, and researchers, helping users focus on deep learning and analysis rather than verifying facts. This commitment to trust and usability has made Liner the tool of choice for more than 10 million users, including students at universities such as UC Berkeley, USC, University of Michigan, and Texas A&M. Liner continues to differentiate itself through partnerships, such as its recent one with Tako, which integrates knowledge visualization tools to present complex data in a more accessible and interactive format, allowing users to delve deeper into their research.
What steps is Liner taking to reduce hallucinations in AI responses, and what impact does this have on user trust?
Reducing hallucinations requires anchoring AI-generated responses to verifiable sources. Liner accomplishes this by cross-referencing its results with academic papers, government databases, and other trusted repositories. Our source filtering system further allows users to exclude unreliable content, providing an additional layer of quality assurance. These steps not only minimize errors but also build trust with your users.
Liner’s system is based on relevance (the score of relevance between an agent-generated claim and a reference passage) and factuality (an assessment of how well a reference passage supports the agent-generated claim). The more supportive the article is, the higher the authenticity score. Since our product strongly encourages users to verify claims to ensure they are not hallucinating, it is critical to enhance the authenticity of our agent system. Ultimately, we observed a positive correlation between factuality scores and user retention.
What steps is Liner taking to build trust among users, especially those who are skeptical of relying on AI for critical information?
Building trust starts with transparency. Liner provides clear references for each result, allowing users to verify the information themselves. Additionally, we rank sources based on reliability and allow users to engage directly with the original content. Continuous user education and open communication also prove that AI, if designed responsibly, can be a reliable ally in education.
What trends do you think will shape the future of artificial intelligence in academic research and expertise retrieval?
AI will become increasingly personalized, adapting to each user’s unique needs and providing tailored insights. Transparency will be key as users seek a clearer understanding of how AI processes information and delivers results. Advances will also focus on addressing information overload and streamlining research tools. By automating repetitive tasks such as data collection and synthesis, AI will speed up the early stages of research, allowing researchers to focus more on critical thinking, analysis and innovation. This balance between efficiency and intellectual engagement will shape the future of academic and professional research.
nearest liner Successfully raised US$29 million in financing. How will this investment help Liner grow? Which areas will you focus on for expansion?
This funding enables us to advance our mission of improving education on artificial intelligence. We’re expanding our global team and rolling out new features like Essay Mode, designed to help students improve their essay writing, structure, and formatting skills. We are also prioritizing partnerships with universities and professional organizations to reach more users and demonstrate the impact of AI-driven research tools. Recent partnerships with companies such as ThetaLabs and Tako expand our capabilities. This investment highlights the growing demand for reliable search solutions and we are eager to build on this momentum.
Thanks for the great interview, readers who want to learn more should visit Liner.
