Dataloop’s automatic annotation tools.
Image Credit: Dataloop
Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Register here.
Following the pandemic, digitalization accelerated and enterprises started investing aggressively in artificial intelligence (AI) and automation to improve their business processes and drive efficiencies. However, when it comes to building an AI project, a company needs to have plenty of well-annotated data to work with. This labeled information is what the system uses to learn, identify patterns and eventually make predictions needed by the end user.
Now, the thing is, data hardly comes annotated by default. It has to be labeled, which can take significant time and resources. In fact, organizations relying on manual data labeling companies can end up spending between hundreds of thousands to upwards of millions of dollars every month just to have their data ready for an AI/ML (machine learning) project.
To address this challenge, Israeli startup Dataloop provides enterprises with an end-to-end platform that covers the entire unstructured data management life cycle for AI projects, starting from data labeling, automating dataops and deploying production pipelines to weaving the human-in-the-loop. The company today announced it has raised $33 million in a series B round of funding, led by NGP Capital and Alpha Wave Ventures.
“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,” Eran Shlomo, CEO at Dataloop, said.
Learn how to build, scale, and govern low-code programs in a straightforward way that creates success for all this November 9. Register for your free pass today.
The company, founded in 2017, first launched annotation capabilities and later expanded to other data management and prep aspects, allowing enterprises to close their data loops faster and shorten the time-to-market for a high-quality AI application.
“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,” Christian Noske, partner at NGP Capital, said. “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 its launch, the company has raised a total of $50M (including this round) and roped in customers such as Intel, Toyota, LinkedIn, and Vimeo. It claims to have seen adoption across industries like retail, agriculture, robotics, autonomous vehicles and construction.
Growing competition in data management and prep
Given that data prep has become such a major component of AI development, multiple platforms and tools have come up to address the challenges organizations face while labeling their datasets. The biggest names in the category are Scale AI and Labelbox, but smaller players like Tasq.ai, SuperAnnotate and Datasaur are also looking to accelerate their roles in the market.
With this round of funding, Dataloop also plans to build its footprint. The company said it will expand the Dataloop platform globally and build teams in the U.S., Europe and India.
According to Research and Markets, the global data annotation market is projected to grow from $695.5 million in 2019 to $6.45 billion by 2027.
VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.