Seoul-based Datumo raises $15.5M to tackle Scale AI, backed by Salesforce

Most organizations say they aren’t absolutely ready to make use of generative AI in a protected and accountable method, based on a current 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 needs to assist companies construct safer AI with instruments and knowledge that allow testing, monitoring, and bettering their fashions—with out requiring technical experience. On Monday the startup raised $15.5 million, which brings its whole raised to roughly $28 million, from buyers together with Salesforce Ventures, KB Funding, and SBI Funding, amongst others.

David Kim, CEO of Datumo and a former AI researcher at Korea’s Company for Defence 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 knowledge of their spare time and earn cash. The startup validated the concept at a startup competitors at KAIST (Korea Superior Institute of Science and Expertise). Kim co-founded Datumo, previously referred to as SelectStar, alongside 5 KAIST alumni in 2018.

Even earlier than the app was absolutely constructed, Datumo secured tens of hundreds of {dollars} in pre-contract gross sales through the buyer discovery part of the competitors, principally 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. Right now, 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 knowledge labeling. The seven-year-old startup now has greater than 300 shoppers in South Korea and generated about $6 million in income in 2024.

“They needed us to attain their AI mannequin outputs or evaluate them to different outputs,” Michael Hwang, co-founder of Datumo, informed TechCrunch. “That’s after we realized: we had 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 informed TechCrunch.

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 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 means of its licensed datasets, significantly knowledge crawled from printed books, which the corporate says presents wealthy structured human reasoning however is notoriously troublesome to wash, based on CEO Kim.

In contrast to its friends, Datumo additionally presents a full-stack analysis platform referred to as Datumo Eval, which routinely generates check knowledge and evaluations to verify for unsafe, biased or incorrect responses with out the necessity for guide scripting, Kim added. The signature product is a no-code analysis instrument 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 smooth dedication. Your entire funding course of took about eight months, Hwang mentioned.

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 international go-to-market operations throughout South Korea, Japan, and the U.S. The startup, which has 150 staff in Seoul, additionally established a presence in Silicon Valley in March.