Jungwon Byun

Elicit is an AI search platform founded in 2021 that focuses on research and information discovery using large language models. The company has developed a search interface that employs AI to help users find, synthesize, and analyze information more efficiently than traditional search engines. Elicit's core approach involves using language models to understand user queries in natural language and surface relevant results alongside AI-generated summaries and insights. The platform targets researchers, academics, and knowledge workers who need to process large volumes of information quickly. Rather than returning simple ranked links, Elicit aims to provide contextual understanding and synthesis of information across sources. The company positions itself in the broader AI search landscape alongside competitors like Perplexity and traditional search engines adapting to AI capabilities. Elicit raised $33M in total funding and maintains a valuation of $100M, operating at Series A stage. The company reflects investor confidence in AI-enhanced search as an alternative to conventional information retrieval. Its technology builds on advances in large language models and retrieval-augmented generation techniques. The company's growth trajectory involves expanding its user base among professionals and institutions that benefit from AI-powered research assistance. Specific customer counts and revenue figures remain undisclosed. Elicit represents one approach to commercializing language models for practical information discovery applications. Elicit applies language models specifically to research and academic information discovery, differentiate itself through synthesis rather than ranking.