Korea’s Flitto Raises USD 23m in IPO

With demand for language data and AI support services on the rise, language data platform Flitto has been readying itself for a listing on the Kosdaq, the Korean electronic trading platform modeled on the US Nasdaq. Flitto tested the waters with potential investors during an oversubscribed demand forecast on July 1 and July 2, 2019.

A couple of weeks later, on July 17, 2019, Flitto began trading on Kosdaq’s development board, which offers a way for companies to join the platform even if they do not as yet meet the requirements for listing on the main board. Flitto’s listing was based on its “promising business model,” and potential to provide value to investors through future scalability.

Slator reached out to Flitto Founder and CEO Simon Lee for more information on the Flitto’s listing and his plans for the company. 

Founded in 2012, Flitto started out as a translation crowdsourcing platform. Thanks to its translation services business, Flitto was able to amass a large corpus of content that has allowed the company to build out its language data offering. According to Lee, “Flitto’s core business is selling linguistic data to AI companies.” 

Meanwhile, the translation services business enables Flitto to collect even more linguistic data. Flitto does this by “agreement from the users on the platform that Flitto will sell the data on behalf of data providers” — both translation buyers and translators, Lee said.

Strong Investor Interest

Flitto’s revenues have increased significantly in recent years, climbing from USD 0.36m in 2015 to USD 4.4m in 2018. 2019 revenues are expected to rise 41% to USD 6.2m.

Lee confirmed that Flitto raised a total of USD 23m from the IPO. The investors were primarily institutional investors (80%) with a number of private investors (20%). Flitto’s market cap currently stands at USD 194m, Lee said.

Lee further told Slator they now plan to set up sales offices in the US and Europe with funds raised from the IPO. In addition, Flitto will develop the company’s platform and proactively build a linguistic database, Lee added. There will also be a focus on R&D efforts in the area of linguistic AI.

Fueling the AI Boom

Lee outlined Flitto’s strategy as “focusing on gathering linguistic data (voice, text, image, video) effectively from the users through Flitto’s web and app platform,” offering users compensation for doing so.

Flitto also partners with third-party companies that develop voice recognition, machine translation, and optical character recognition (or OCR) software, among others. “If AI companies are car manufacturers, Flitto is an oil company,” Lee said.

As demonstrated by language data market leader Appen’s strong first half performance, demand for AI support services and curated language data is strong and shows no sign of slowing. Shares in Australian-listed Appen doubled in the six months to June 2019, and the company finished the first half with more than USD 2bn in market cap.

The current surge in demand equates to an “AI boom era,” Flitto’s Lee said of the growing language data market. “More companies are jumping into the language AI market. Even SMEs are developing their own AI engines to deal with global users and clients. Thousands of AI techs are being developed but [there is] not enough data to train those AIs,” he said. Lee’s prediction, therefore, is that “the demand for language data will grow.”

As a listed company, Flitto is now required to report on its performance on a quarterly basis. Slator will track Flitto’s performance along with fellow language data company Appen and the handful of listed language service providers (LSPs) that include RWS, SDL, Keywords, ZOO Digital, Rozetta, Honyaku Center and Straker.

Appen CEO Mark Brayan will speak at SlatorCon San Francisco on September 12, 2019.

Slator 2019 Language Industry M&A and Funding Report

34-page report. Language industry M&A and startup funding. Transaction valuations, trade sales, financial backing, private equity influence, main rationale, seller verticals, geographical analysis, startup funding analysis.