Datumo Raises $15.5M to Enhance AI Safety and Evaluation

Datumo Secures $15.5M to Champion Safer AI

The artificial intelligence landscape is rapidly evolving, with generative AI at the forefront. However, a significant hurdle remains: ensuring these powerful tools are used safely and responsibly. A recent McKinsey report highlights that a majority of organizations feel unprepared to implement generative AI ethically. A key concern is the explainability of AI decisions – understanding the 'why' and 'how' behind an AI's output. While 40% of respondents identify this as a major risk, a mere 17% are actively working to address it.

Enter Datumo, a Seoul-based company that began its journey in AI data labeling and is now poised to help businesses build more robust and trustworthy AI systems. With its latest funding round, Datumo aims to provide the essential tools and data for testing, monitoring, and refining AI models, crucially without demanding deep technical expertise from its clients. This $15.5 million infusion, which brings their total funding to approximately $28 million, comes from notable investors including Salesforce Ventures, KB Investment, ACVC Partners, and SBI Investment.

From Data Labeling to AI Trust: Datumo's Evolution

The genesis of Datumo, formerly known as SelectStar, lies in the frustration of its CEO, David Kim, a former AI researcher at Korea’s Agency for Defense Development. Kim recognized the sheer time and effort involved in data labeling. His innovative solution? A reward-based app designed to allow individuals to contribute to data labeling in their spare time while earning money. This novel concept was not only validated but also garnered significant traction during a startup competition at KAIST (Korea Advanced Institute of Science and Technology). Kim, along with five KAIST alumni, co-founded Datumo in 2018.

The early days were marked by impressive success. Even before the app was fully developed, Datumo secured substantial pre-contract sales, largely from businesses led by KAIST alumni. In its inaugural year, the startup achieved over $1 million in revenue, solidifying key client relationships. Today, Datumo boasts an impressive roster of clients, including major South Korean enterprises such as Samsung, Samsung SDS, LG Electronics, LG CNS, Hyundai, Naver, and SK Telecom. The company's evolution didn't stop at data labeling; as clients began requesting more advanced services, Datumo pivoted.

"They wanted us to score their AI model outputs or compare them to other outputs," explained Michael Hwang, co-founder of Datumo. "That’s when we realized: We were already doing AI model evaluation — without even knowing it." This realization prompted Datumo to significantly invest in AI model evaluation, leading to the release of Korea’s first benchmark dataset specifically focused on AI trust and safety. "We started in data annotation, then expanded into pretraining datasets and evaluation as the LLM ecosystem matured," Kim elaborated.

The market for AI data and evaluation is clearly heating up, underscored by Meta’s substantial $14.3 billion investment in data-labeling company Scale AI. This move highlights the critical role of quality data in AI development. Interestingly, in the wake of this deal, OpenAI ceased using Scale AI’s services, indicating the competitive and dynamic nature of this sector. Datumo finds itself in a competitive space, sharing common ground with companies like Scale AI in dataset provisioning, and with platforms such as Galileo and Arize AI in AI evaluation and monitoring.

Datumo's Unique Value Proposition

What sets Datumo apart in this crowded field? The company offers licensed datasets, notably data meticulously crawled from published books. According to CEO Kim, this data source provides rich, structured human reasoning, though it presents significant challenges in terms of data cleaning – a process Datumo excels at.

Furthermore, Datumo introduces Datumo Eval, a comprehensive, full-stack evaluation platform. This innovative tool automates the generation of test data and evaluations to rigorously check AI models for unsafe, biased, or incorrect responses, all without the need for manual scripting. The platform’s signature product is its no-code evaluation tool, specifically designed for non-developers, including those in policy, trust and safety, and compliance teams. This accessibility democratizes AI safety and evaluation.

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Fueling Growth and Global Reach

Attracting investors like Salesforce Ventures wasn't an overnight process. Kim recounted how a fireside chat with Andrew Ng, founder of DeepLearning.AI, at a South Korean event led to a LinkedIn post that captured the attention of Salesforce Ventures. Following extensive meetings and discussions, the investors extended a soft commitment, culminating in an eight-month funding process.

The newly acquired capital will be instrumental in accelerating Datumo's research and development, with a particular focus on advancing automated evaluation tools for enterprise AI. The funding will also fuel the expansion of Datumo's global go-to-market operations across South Korea, Japan, and the United States. With a team of 150 employees in Seoul, Datumo has also established a strategic presence in Silicon Valley, positioning itself for broader international impact.

In a world increasingly reliant on AI, ensuring its safety, fairness, and reliability is paramount. Datumo’s mission to build trust in AI resonates deeply, particularly for businesses aiming to harness AI's power responsibly. As AI adoption accelerates across industries, solutions that simplify complex challenges in AI development and deployment will be crucial for success.

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