Most organizations say they aren’t absolutely ready to make use of generative AI in a secure and accountable manner, in keeping with a latest McKinsey report. One concern is explainability — understanding how and why AI makes sure choices. Whereas 40% of respondents view it as a big threat, solely 17% are actively addressing it, per the report.
Seoul-based Datumo started as an AI knowledge labeling firm and now desires to assist companies construct safer AI with instruments and knowledge that allow testing, monitoring, and enhancing 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 buyers 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 Improvement, was annoyed 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 knowledge of their spare time and earn cash. The startup validated the thought 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 absolutely constructed, Datumo secured tens of 1000’s of {dollars} in pre-contract gross sales in the course of the buyer discovery part of the competitors, largely from KAIST alumni-led companies and startups.
In its first yr, the startup surpassed $1 million in income and secured a number of key contracts. At the moment, 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 purchasers. A number of years in the past, nevertheless, purchasers started asking the corporate to transcend easy knowledge labeling. The 7-year-old startup now has greater than 300 purchasers in South Korea and generated about $6 million in income in 2024.
“They wished us to attain their AI mannequin outputs or evaluate them to different outputs,” Michael Hwang, co-founder of Datumo, instructed TechCrunch. “That’s once we realized: We have been already doing AI mannequin analysis — with out even figuring out 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 knowledge annotation, then expanded into pretraining datasets and analysis because the LLM ecosystem matured,” Kim instructed TechCrunch.
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Meta’s latest $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 providers. The Meta deal additionally alerts that competitors for AI coaching knowledge 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, significantly knowledge crawled from printed books, which the corporate says presents wealthy structured human reasoning however is notoriously tough to wash, in keeping with CEO Kim.
Not like its friends, Datumo additionally presents a full-stack analysis platform known as Datumo Eval, which robotically generates take a look at knowledge and evaluations to examine for unsafe, biased or incorrect responses with out the necessity for guide scripting, Kim added. The signature product is a no-code analysis software designed for non-developers like these on coverage, belief and security, and compliance groups.
When requested about attracting buyers like Salesforce Ventures, Kim defined that the startup had beforehand hosted a fireplace 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 buyers prolonged a mushy dedication. Your entire funding course of took about eight months, Hwang stated.
The brand new funding might be used to speed up R&D efforts, significantly in creating automated analysis instruments for enterprise AI, and to scale world 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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