Seoul -based Datomo in collaboration with Sales Force to take AI on a scale .55m increased,

Most organizations say they are not fully prepared to use Generative AI in a safe and responsible manner, According to a recent report of McKeni. There is a concern – understanding how and why AI makes certain decisions. While 40 % of respondents view it as an important threat, according to this report, only 17 % are actively resolved.

Based on the seoul Datomo AI data labeling has been launched as a company and now want businesses to help build a safe AI with tools and data that enables them to test, monitor and improve their models, without the need for technical skills. On Monday, Startup raised $ 15.5 million, which deposits its total amount, including sales force ventures, KB investment, ACVC partners, and investors, including SBI investment.

Detomo’s CEO David Kim and former AI researcher of the Korean Agency for Defense Development, who were disappointed with the data labeling time, brought a new idea: a rewards app that allows anyone to label data and make money in their spare time. Startup confirmed the idea in a start -up competition at Kyst (Korea Advanced Institute of Science and Technology). Kim jointly, as well as the Datomo, known as the Select Star, as well as five cassettes in 2018 with former students.

Even before the app was fully constructed, Datomo received thousands of dollars in sale of thousands of dollars during the competition customer discovery phase, mostly from businesses and startups led by former Kista students.

In his first year, Startup crossed $ 1 million in revenue and made several important agreements. Today, Startup has counted major Korean companies such as Samsung, Samsung SDS, LG Electronics, LGCNS, Hyundi, Neur, and Seoul -based telecommunications Giant Telecom. However, many years ago, clients began to ask the company to go beyond the easy data labeling. The 7 -year -old Startup now has more than 300 clients in South Korea and has earned about $ 6 million in 2024.

“They wanted us to score or compare them with other results,” said Michael Huang, co -founder of the Datomo, Michael Huang, Tech Crunch, told Tech Crunch. “Only when we felt: We were already diagnosed with the AI model. Huang added that Datomo doubled the area and issued Korea’s first bench mark Dataset, which focuses on the AI Trust and Safety.

Kim told Tech Crunch, “We started the explanation of the data, then expanded the default datases and diagnosis as the LLM environmental system was solid.”

Meta’s recent .3 investment data labeling company highlights the importance of this market at Scale AI, such as acquiring $ 14.3 billion. Immediately after the deal, the AI model maker and Meta’s opponent Openai stopped using AI services on a scale. Meta Dell also indicates that AI training data is intensifying.

Datomo Datastate has some matches with companies like Scale AI, and AI in the diagnosis and monitoring of Galileo and AI. However, it differentiates itself through its licensed datases, especially the data that has been reached from the published books, which the company says, according to the CEO, says the company offers a rich human reasoning but it is difficult to clear it.

Unlike his peers, Datomo also offers a full -fledged stack diagnostic platform called Datomo EvilKim added, which automatically develops test data and diagnosis to check unsafe, biased or wrong reactions without the need for manual scripting. The signature product is designed for non -developers such as policy, confidence and safety, and compliance teams.

When asked about attracting investors such as sales force ventures, Kim explained that a South Korean program had hosted a fire -chat with Andrew NG, the founder of the Department of Development Dot, in a South Korean program. After the event, Kim shared the session on LinkedIn, which attracted the attention of sales force ventures. After numerous meetings and zoom calls, investors increased their commitment. Huang said the entire funding process took about eight months.

New funding will be used to accelerate R&D efforts, especially in the manufacture of automatic diagnostic tools for enterprise AI, and to measure global market operations in South Korea, Japan, and the United States, which have 150 employees in Seoul, Silicon Valley in March.

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