DataLoop

Name: DataLoop
Brand: Dataloop
Rating: 4.4 (91 reviews)

The AI-ready Data Stack

Est 2017|Valuation $120M|Raised $49.3M|28 Ref Customers

LinkedIn 10K|Web traffic 22K|FTEs 52|HQ Herzliya, Tel-Aviv District, IL

MarketsData Labeling

Dataloop vs Labelbox - Labelbox provides a free tier and a unit-based pricing model that can lower friction for pilots and evaluations. - Labelbox marketing positions Dataloop as a more technical option; that positioning is inherently biased and should be validated through trials and customer references. Dataloop vs Scale AI - Scale AI is widely described as a large provider for labeling and data services with extensive managed operations. - Scale’s Rapid documentation includes structured pricing mechanics for certain tasks, but does not substitute for direct pricing discussions. Market trend context: The labeling and evaluation market has evolved with generative AI and multimodal workloads; service quality, security posture, and cost predictability are key differentiators.

01Competitive Landscape

Narrative analysis

Dataloop vs Labelbox

Labelbox provides a free tier and a unit-based pricing model that can lower friction for pilots and evaluations.
Labelbox marketing positions Dataloop as a more technical option; that positioning is inherently biased and should be validated through trials and customer references.

Dataloop vs Scale AI

Scale AI is widely described as a large provider for labeling and data services with extensive managed operations.
Scale’s Rapid documentation includes structured pricing mechanics for certain tasks, but does not substitute for direct pricing discussions.

Market trend context: The labeling and evaluation market has evolved with generative AI and multimodal workloads; service quality, security posture, and cost predictability are key differentiators.

	Dataloop	Labelbox	Scale AI (Rapid / Services)
Starting Price	Not publicly listed (demo-led)	Offers free tier; paid subscription/usage units	Pricing varies by task/services; not simple public SaaS tiers
Typical Use Case	Teams needing integrated unstructured data management, annotation, and pipeline automation	Teams seeking a user-friendly labeling UI, curation/catalog features, and model evaluation tooling	Organizations outsourcing labeling at scale with strong managed services
Key Strength	Emphasizes SDK/API-driven automation and pipeline integration	Free tier availability, clear unit model, and broad multimodal tooling	Broad managed services capability and enterprise procurement motion
Key Weakness	Pricing transparency is limited; platform may require engineering investment; some reviews note stability/performance issues	Unit-based pricing can be hard to forecast at scale	Dependency on managed services can affect cost predictability and operational control