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Dataloop AI has raised $44.0M across 2 funding rounds.
Key people at Dataloop AI.
Dataloop AI has raised $44.0M in total across 2 funding rounds.
Based in Herzliya, Israel, Dataloop AI provides a comprehensive software-as-a-service platform and data infrastructure system designed to manage unstructured data throughout the artificial intelligence development lifecycle. The enterprise software enables machine learning teams to execute complex data labeling, automate processing pipelines, and integrate human feedback into deep learning and computer vision models. Prior to its acquisition, the company scaled its operations to include over 80 employees and secured approximately $50 million in total venture capital funding, which included a $33 million Series B round. The technology has been utilized by corporate customers such as Vimeo and Syngenta, and the business was backed by institutional investors including NGP Capital and Alpha Wave Global before being acquired by Dell Technologies for $120 million in 2025. Dataloop AI was founded in 2017 by Eran Shlomo, Avi Yashar, and Nir Buschi.
Dataloop AI has raised $44.0M in total across 2 funding rounds.
Dataloop AI's investors include Kima Ventures, NGP Capital, Maxime Paradis, Michael Benabou, 91 Ventures, Amino Collective, LocalGlobe, OurCrowd, Trivian Capital, Webtalk Ltd, Noah Pickholtz.
Dataloop AI has raised $44.0M across 2 funding rounds. Most recently, it raised $33.0M Series B in November 2022.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Nov 1, 2022 | $33M Series B | — | Kima Ventures, NGP Capital, Maxime Paradis, Michael Benabou | Announced |
| Oct 1, 2020 | $11M Series A | — | 91 Ventures, Amino Collective, LocalGlobe, OurCrowd, Trivian Capital, Webtalk LTD, Noah Pickholtz | Announced |
Dataloop AI is an Israeli technology company founded in 2017 that provides an enterprise-grade platform for managing the full AI development lifecycle, focusing on unstructured, multimodal data to make AI accessible to developers and data teams.[1][2][3][4] Its core product is a data-centric AI stack that enables teams to build, orchestrate, train, evaluate, deploy, and scale AI models through intuitive no-code workflows, drag-and-drop interfaces, pre-built nodes, data catalogs, and human-in-the-loop feedback loops, serving enterprises in sectors like autonomous driving, NLP, ADAS, and government agencies.[1][2][4] Dataloop solves the challenges of data silos, manual preparation of complex data, and collaboration barriers in AI pipelines, delivering 20x faster development, higher quality datasets, and near-zero manual work while prioritizing privacy and security standards.[2][4] As a mature-stage company with 51-100 employees, ~$13M in estimated revenues, and $49M raised, it shows strong growth through partnerships like Government Acquisitions Inc. (GAI) and Carahsoft for public sector AI adoption.[1][4][6]
Dataloop was established in 2017 in Herzliya, Israel, on the foundational insight that AI's essence lies in data, aiming to democratize the entire AI development cycle for developers regardless of data science expertise.[1][3] While specific founders are not detailed in available sources, the company's early vision centered on bridging gaps between data specialists, developers, and engineers through a collaborative, intuitive platform that integrates data, models, apps, and human insights.[1][2] Pivotal early traction came from addressing real-world needs in high-stakes AI applications, such as improving ADAS/autonomous driving datasets, scaling ASR/NLP projects, and weekly model refinements in classification tasks, earning praise from R&D leads and CTOs at adopting enterprises.[2] This data-centric approach quickly positioned Dataloop as a key enabler for production-ready AI, evolving into a robust infrastructure supporting multimodal data at scale.[4]
Dataloop rides the explosive growth of generative AI and agentic systems, where unstructured data (e.g., images, audio, video) dominates training needs but poses massive preparation hurdles—market forces like surging multimodal AI demand and regulatory pushes for secure data handling amplify its timing.[2][4] By providing a unified data stack, it accelerates AI from raw inputs to production models, influencing the ecosystem through partnerships with government integrators like GAI and Carahsoft, enabling federal agencies to build efficient, compliant AI for decision-making and operations.[4][6] In a landscape shifting toward data infrastructure as the bottleneck (beyond just models), Dataloop fosters a "data-centric culture," empowering non-hyperscale players to compete and driving broader adoption in enterprise and public sectors.[1][2]
Dataloop is poised to expand as the AI data infrastructure leader, capitalizing on agentic AI trends, government AI mandates, and multimodal data explosion with deeper public sector penetration and enterprise wins. Trends like autonomous agents, real-time feedback scaling, and hybrid cloud AI will shape its path, potentially boosting revenues beyond $13M through strategic alliances. Its influence may evolve from pipeline enabler to ecosystem orchestrator, keeping humans in control amid accelerating AI complexity—reinforcing its founding mission to make AI development truly accessible for all.[1][2][4]
Key people at Dataloop AI.
