Highlights:

  • The 2017-founded startup originally introduced annotation capabilities and then expanded to other data management and prep aspects.
  • Dataloop intends to expand its footprint with the help of this round of funding.

After the pandemic, with an increase in digitalization, businesses started investing heavily in Artificial Intelligence (AI) and automation to enhance business operations and increase efficiency. But to work when developing an AI project, a corporation must have thoroughly annotated data to work with. The system uses this labeled data to learn, identify trends, and finally generate the predictions the user will need.

The fact is that data isn’t typically annotated by default. It needs to be labeled, which can take sufficient time and money. Businesses that rely on manual data labeling companies may end up paying between a few hundred thousand dollars and as much as a million dollars per month to get their data ready for an AI/ML (machine learning) project.

Enter Dataloop

To resolve this issue, Israeli startup Dataloop offers businesses an end-to-end platform that covers the entire unstructured data management life cycle for AI projects, from data labeling, automating dataops, and deploying production pipelines to weaving the human-in-the-loop. This platform addresses the challenge of managing unstructured data for AI projects. Today, the business disclosed that it had raised USD 33 million in a series B round of fundraising, with NGP Capital and Alpha Wave Ventures serving as lead investors.

Eran Shlomo, CEO of Dataloop, said, “The Dataloop platform helps businesses of any size to move their AI project into production, from start to finish. We are working to break through the limitations of AI development and create efficient workflows, easy-to-use management systems, and accurate annotation tools, so teams of all industries can use them.”

The 2017-founded startup originally introduced annotation capabilities and then expanded to other data management and prep aspects, permitting businesses to close their data loops more quickly and minimize the time it takes to market for a high-quality AI application.

Christian Noske, the partner at NGP Capital, said, “Dataloop has pinpointed a large obstacle in an important and fast-growing market. Most companies these days have a dedicated team working on data management and AI integrations, and they all face the same challenges. Dataloop has built a great platform that will have a significant impact on the AI production industry as a whole. We look forward to working with the Dataloop team to drive forward further global expansion.”

Since it was founded, the company has raised USD 50 million (including this round) in funding and signed on clients, including Intel, Toyota, LinkedIn, and Vimeo. It claims to have seen adoption across industries like retail, agriculture, robotics, autonomous vehicles, and construction.

Increasing competition in data preparation and management

Given that data preparation has become a significant part of AI development, numerous platforms and solutions have been developed to address businesses’ difficulties while labeling their datasets. Scale AI and Labelbox are the two most well-known brands in the market, although smaller players like Tasq.ai, SuperAnnotate, and Datasaur are also attempting to expand their market share.

Dataloop intends to expand its footprint with the help of this round of funding. The business announced that it would establish teams in the United States, Europe, and India and grow the Dataloop platform globally.

According to Research and Markets, the global market for data annotation is anticipated to increase from USD 695.5 million in 2019 to USD 6.45 billion by 2027.