Most organizations say they aren’t totally ready to make use of generative AI in a secure and accountable method, in accordance with a current McKinsey report. One concern is explainability — understanding how and why AI makes sure choices. Whereas 40% of respondents view it as a major danger, solely 17% are actively addressing it, per the report.
Seoul-based Datumo started as an AI information labeling firm and now needs to assist companies construct safer AI with instruments and information that allow testing, monitoring, and bettering their fashions — with out requiring technical experience. On Monday the startup raised $15.5 million, which brings its complete raised to roughly $28 million, from traders together with Salesforce Ventures, KB Funding, ACVC Companions, and SBI Funding, amongst others.
David Kim, CEO of Datumo and a former AI researcher at Korea’s Company for Protection Growth, was pissed off by the time-consuming nature of knowledge labeling so he got here up with a brand new concept: a reward-based app that lets anybody label information of their spare time and earn cash. The startup validated the concept at a startup competitors at KAIST (Korea Superior Institute of Science and Know-how). Kim co-founded Datumo, previously often known as SelectStar, alongside 5 KAIST alumni in 2018.
Even earlier than the app was totally constructed, Datumo secured tens of hundreds of {dollars} in pre-contract gross sales throughout the buyer discovery part of the competitors, principally from KAIST alumni-led companies and startups.
In its first 12 months, the startup surpassed $1 million in income and secured a number of key contracts. At present, the startup counts main Korean firms like Samsung, Samsung SDS, LG Electronics, LG CNS, Hyundai, Naver, and Seoul-based telecom big SK Telecom amongst its shoppers. A number of years in the past, nonetheless, shoppers started asking the corporate to transcend easy information labeling. The 7-year-old startup now has greater than 300 shoppers in South Korea and generated about $6 million in income in 2024.
“They wished us to attain their AI mannequin outputs or examine them to different outputs,” Michael Hwang, co-founder of Datumo, informed TechCrunch. “That’s once we realized: We have been already doing AI mannequin analysis — with out even realizing it.” Datumo doubled down on this space and launched Korea’s first benchmark dataset centered on AI belief and security, Hwang added.
“We began in information annotation, then expanded into pretraining datasets and analysis because the LLM ecosystem matured,” Kim informed TechCrunch.
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co-founders of datumoPicture Credit:Datumo
Meta’s current $14.3 billion acquisition-like funding in data-labeling firm Scale AI highlights the significance of this market. Shortly after that deal, AI mannequin maker and Meta competitor OpenAI stopped utilizing Scale AI’s companies. The Meta deal additionally alerts that competitors for AI coaching information is intensifying.
Datumo shares some similarities with firms like Scale AI in pretraining dataset provisioning, and with Galileo and Arize AI in AI analysis and monitoring. Nevertheless, it differentiates itself by way of its licensed datasets, notably information crawled from printed books, which the corporate says presents wealthy structured human reasoning however is notoriously tough to wash, in accordance with CEO Kim.
In contrast to its friends, Datumo additionally presents a full-stack analysis platform known as Datumo Eval, which robotically generates take a look at information and evaluations to test for unsafe, biased or incorrect responses with out the necessity for guide scripting, Kim added. The signature product is a no-code analysis device designed for non-developers like these on coverage, belief and security, and compliance groups.
When requested about attracting traders like Salesforce Ventures, Kim defined that the startup had beforehand hosted a hearth chat with Andrew Ng, founding father of DeepLearning.AI, at an occasion in South Korea. After the occasion, Kim shared the session on LinkedIn, which caught the eye of Salesforce Ventures. Following a number of conferences and Zoom calls, the traders prolonged a tender dedication. Your complete funding course of took about eight months, Hwang mentioned.
The brand new funding might be used to speed up R&D efforts, notably in creating automated analysis instruments for enterprise AI, and to scale international go-to-market operations throughout South Korea, Japan, and the U.S. The startup, which has 150 workers in Seoul, additionally established a presence in Silicon Valley in March.
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