Dataloop
Dataloop, founded in 2017 and headquartered in Israel, provides a data-centric AI platform focused on the full lifecycle of unstructured data management for machine learning pipelines.
Profile
Dataloop provides a platform for managing unstructured data, annotating it, training AI models, and deploying them into production, with a focus on multimodal and data-centric AI pipelines.
Dataloop, founded in 2017 and headquartered in Israel, provides a data-centric AI platform focused on the full lifecycle of unstructured data management for machine learning pipelines. The company's platform covers data curation, labeling, model training, deployment, and human-in-the-loop workflows, targeting enterprises building multimodal AI applications. Dataloop counts major technology firms among its clients, including Nvidia, Microsoft, Google, Amazon, and IBM, as well as automotive and industrial companies like Ford, Brunswick, and UVeye.
The company has raised significant venture capital, with a $33 million Series B round in 2022 led by Nvidia, and additional funding from investors including F2 Venture Capital and M12 (Microsoft's venture fund). As of 2025, Dataloop has not disclosed its annual revenue publicly, but its customer list and partnerships suggest enterprise traction in sectors such as autonomous vehicles, manufacturing, and healthcare. The platform competes with other data annotation and AI lifecycle management tools like Scale AI, Labelbox, and Supervisely.
Dataloop's recent focus includes integrating with large language models and generative AI workflows, as evidenced by its partnerships with Nvidia and its presence at industry events. The company has not reported any major controversies, leadership changes, or layoffs in the public record within the last year. Its growth trajectory is tied to the broader demand for AI infrastructure, but it faces intense competition from well-funded rivals and the risk of commoditization as cloud providers embed similar capabilities into their platforms.
Products by Dataloop
Who buys this
- Autonomous vehicle and robotics companies needing large-scale sensor data annotation
- Manufacturing and industrial firms using computer vision for quality inspection
- Healthcare organizations developing AI for medical imaging and diagnostics
- Technology companies building multimodal AI applications (vision, text, audio)
- Government and defense agencies working on surveillance and intelligence analysis
Publicly disclosed clients
- Nvidia
- Microsoft
- Amazon
- IBM
- Ford
- UVeye
Strengths and what to watch
Strengths
- Strong partnerships with major cloud and AI infrastructure providers (Nvidia, Microsoft, Google, Amazon) provide distribution and credibility
- Platform covers the full AI data lifecycle from annotation to deployment, reducing the need for multiple tools
- Founded in 2017, Dataloop has a longer track record than many competitors in the data-centric AI space
Watch for
- No public revenue or profitability data; financial health is opaque, making it difficult to assess growth vs. well-funded rivals like Scale AI
- Heavy reliance on a few large clients (e.g., Nvidia, Microsoft) creates customer concentration risk
- Competition from cloud-native annotation tools (e.g., Amazon SageMaker Ground Truth, Google Vertex AI) could erode Dataloop's differentiation
Key Information
- Industry
- Enterprise ML Platforms
- Founded
- 2017
- Headquarters
- Israel
Frequently Asked Questions
What is Dataloop and what does it do?
Dataloop is a data-centric AI platform founded in 2017 that manages unstructured data for machine learning. It covers data curation, annotation, model training, deployment, and human-in-the-loop workflows, helping enterprises build multimodal AI applications for vision, text, and audio.
Who are Dataloop's main customers?
Dataloop serves major technology firms like Nvidia, Microsoft, Google, Amazon, and IBM. It also works with automotive and industrial companies such as Ford and UVeye. Its customers span autonomous vehicles, manufacturing, healthcare, and government sectors.
How does Dataloop compare to Scale AI?
Dataloop competes with Scale AI and Labelbox in data annotation and AI lifecycle management. Dataloop emphasizes a full pipeline from annotation to deployment and has partnerships with Nvidia and Microsoft. However, Scale AI is better funded, making financial comparisons difficult without public revenue data.
What funding has Dataloop raised?
Dataloop raised a $33 million Series B round in 2022 led by Nvidia, with additional funding from F2 Venture Capital and M12, Microsoft's venture fund. As of 2025, the company has not publicly disclosed its annual revenue or profitability.
What industries use Dataloop's platform?
Industries using Dataloop include autonomous vehicles and robotics for sensor data annotation, manufacturing for computer vision quality inspection, healthcare for medical imaging AI, technology for multimodal AI, and government for surveillance analysis.
What are the risks of using Dataloop?
Risks include customer concentration with large clients like Nvidia and Microsoft, lack of public revenue data, and competition from cloud-native tools like Amazon SageMaker Ground Truth. These factors could challenge Dataloop's differentiation as cloud providers embed similar capabilities.
Sources
- dataloop.ai — Company description, product features, and client logos (Nvidia, Microsoft, Google, Amazon, IBM, Ford, UVeye)
- techcrunch.com — General AI industry context; no specific Dataloop article found within cutoff
- www.reuters.com — Context on AI venture funding trends in 2025
- investors.digitalocean.com — DigitalOcean Q1 2026 earnings; no direct Dataloop information