Join us on November 9 to learn how to successfully innovate and achieve efficiency by upscaling and scaling citizen developers at the Low-Code/No-Code Summit. Register here.
After the pandemic, digitalization accelerated and companies began investing aggressively in artificial intelligence (AI) and automation to improve their business processes and increase efficiency. 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 ultimately make predictions that the end user needs.
The thing is, data is hardly annotated by default. It has to be labeled, which can take a lot of time and resources. Organizations that rely on manual data labeling companies can end up spending hundreds of thousands to more than millions of dollars per month getting their data ready for an AI/ML (machine learning) project.
Enter Data Loop
To meet this challenge, the Israeli startup data loop provides enterprises with an end-to-end platform that covers the entire lifecycle of unstructured data management for AI projects, from data labeling, data ops automation and deployment of production pipelines to weaving the human-in-the-loop. The company announced today that it has raised $33 million in a Series B financing round led by NGP Capital and Alpha Wave Ventures.
“The Dataloop platform helps companies of all sizes take their AI project 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 that teams from all industries can use them,” said Eran Shlomo, CEO of Dataloop.
Event
Top with little code/no code
Learn how tobuild, scale, and manage low-code programs in a simple way that makes it all a success. Nov 9register your free pass today.
Register here
Founded in 2017, the company first launched annotation capabilities and later expanded into other data management and preparation aspects, enabling enterprises to close their data loops faster and reduce time to market for a high-performance AI application.
“Dataloop has located a major obstacle in an important and fast-growing market. Most companies today have a dedicated team working on data management and AI integrations, and they all face the same challenges,” said Christian Noske, partner at NGP Capital. “Dataloop has built an amazing platform that will have a significant impact on the AI manufacturing industry as a whole. We look forward to working with the Dataloop team to drive further global expansion.”
Since its launch, the company has raised a total of $50 million (including this round) and brought in clients such as Intel, Toyota, LinkedIn and Vimeo. It claims to have been adopted in sectors such as retail, agriculture, robotics, autonomous vehicles and construction.
Increasing competition in data management and preparation
As data preparation has become such an important part of AI development, multiple platforms and tools have been developed to address the challenges organizations face when labeling their data sets. The biggest names in the category are Scale AI and Labelbox, but smaller players such as Tasq.ai, SuperAnnotate and Datasaur also want to accelerate their role in the market.
With this funding round, Dataloop also plans to build its footprint. The company said it will expand the Dataloop platform globally and build teams in the US, Europe and India.
According to Research and Markets, the global data annotation market is expected to grow from $695.5 million in 2019 to $6.45 billion in 2027.
The mission of VentureBeat is a digital city square for tech decision makers to gain knowledge about transformative business technology and transactions. Discover our briefings.
Janice has been with businesskinda for 5 years, writing copy for client websites, blog posts, EDMs and other mediums to engage readers and encourage action. By collaborating with clients, our SEO manager and the wider businesskinda team, Janice seeks to understand an audience before creating memorable, persuasive copy.