Felo

Felo Search is the AI answer engine that distinguishes itself in a crowded category through multilingual reach and source quality: built by a Japanese-Korean team with global search ambitions, it handles queries in dozens of languages with retrieval that genuinely searches the relevant language's web — not just English sources translated after the fact. Ask in Arabic, Japanese, or Spanish and receive answers grounded in native-language sources with citations, which for non-English research is the difference between real information and translation artifacts.

The product mechanics follow the established answer-engine pattern executed competently: synthesized answers with inline citations, follow-up questioning that preserves context, an agent mode that runs deeper multi-step research, and organized collections for saving and sharing results. The mind-map visualization of answers — showing the structural relationships in the information retrieved — is a distinctive touch for research synthesis. In our comparative testing, Felo held its own against Perplexity on standard queries and clearly beat global competitors on Asian-language and cross-language retrieval tasks.

Honest limits: index depth trails the category leader on obscure English-language technical queries; the free tier's model access is limited with Pro (~$20/month) unlocking the frontier options; and ecosystem features (API, deep platform integrations) are younger than competitors'. For multilingual users, researchers working across languages, and anyone whose information needs live outside the English web, Felo fills a real gap the category leader serves less well. For pure English technical research, the comparison deserves a fair trial on both sides.