Who is EarlGrid?
EarlGrid Inc. is a mission-driven company committed to building a cross-lingual knowledge graph of proper names. We are a global team, born in Silicon Valley with an Asia hub in Busan, Korea in June 2026.

What does EarlGrid do?
We construct the data infrastructure for names, so that AI can hear a name right, find it instantly, and understand what it actually points to. Engineers call these proper names 'named entities.'

Do names matter?
Proper names (named entities) often carry more meaning than any other word or phrase in a sentence. Take "EarlGrid was born in California." The words "EarlGrid" and "California" give you a more vibrant picture of the information than just "born" or "company" do. Or take "That person appeared in the movie Interstellar." The title Interstellar points to exactly one thing in the world, and that sharpness gives it more significant information than the other phrases and words such as "that person," "appeared," "in," or "the movie."

Why is AI bad with names?
Names come in many shapes from brand names and product names to titles of songs, films, series, and games as well as names of people, places, institutions, and companies. These are the words that carry the core information in human communication. And these are exactly the words AI gets wrong more frequently than we want. The rarer and the more distinct the name, the worse AI does with it. Here lies the paradox: a name exists to pick out one single thing in the world, so by nature it has to be unique. That very uniqueness pushes it outside the patterns in AI's training data, and AI struggles to recognize it.

What our founder saw
Machines have been struggling with names for as long as they have been listening. One founder spent nearly two decades noticing this up close. Early on, she transliterated geotags into Korean for a Fortune 500 company in the Bay Area, and watched place names break navigation for Korean users. Later, working on titles for a global streaming platform, she saw key names and phrases (a.k.a. KNPs) come through inconsistent across languages, and saw how much time and money it took to fix them one at a time. At some point, noticing was not enough.

Two tries
Around 2023 she drew up a business plan for a cross-lingual name search engine called Name Flipper. It did not go anywhere. In 2024 and 2025 she tried again as Name Map. A strategy consultant asked her to show there was a market for getting proper names right, and she could not, so she stopped. She knows how to measure that now. Back then she was running Culture Flipper, a global localization company. Every month there started with the same question: whether there was enough money coming in to pay everyone, and answering it left very little of her for anything else.

The decision
So she closed the company she had given 9+ years of her life to, and started the one she needed. EarlGrid is that company, built slowly with people who care about getting things right. We build the cross-lingual named-entity knowledge base that speech AI should have had from the start, at the point where linguistics, speech AI, and content intelligence meet.

Our path
We fell often, and we still do. We just get up and keep walking, and the path is whatever is behind us.