World Labs vs Intello Labs

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. World Labs employs 50-200 people, while Intello Labs has 50-200 employees.

World Labs has raised more in total funding at $230M, compared to Intello Labs's $10M — a gap of $220M.

World Labs holds the higher Awaira Score at 75/100, compared to Intello Labs's 55/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 20-point gap that reflects meaningful differences in scale or traction.

World Labs was founded by Fei-Fei Li in 2024. Intello Labs was founded by Abhishek Middha in 2016. Visit each company's profile on Awaira for a full founder biography.

World Labs: World Labs is an AI research and product company building spatial intelligence systems capable of generating, understanding, and reasoning about three-dimensional worlds. The company is developing large world models (LWMs) that can produce coherent, physically plausible 3D environments from images or descriptions, with intended applications in gaming, simulation, robotics, and creative media.\n\nThe company raised approximately 230 million USD in one of the largest Series A rounds in AI history, backed by leading venture capital firms attracted by the technical credentials of its founding team. World Labs was founded by Fei-Fei Li, the Stanford AI Lab director widely credited with creating ImageNet, the benchmark dataset that catalyzed the deep learning revolution in computer vision.\n\nSpatial AI and 3D world generation represent a frontier capability with applications across multiple large markets including video game development, architectural visualization, autonomous vehicle simulation, and virtual production. The founding team technical pedigree and the scale of initial funding position World Labs as one of the most watched early-stage AI companies, with the expectation that breakthrough spatial intelligence capabilities could redefine how 3D content is created and how AI systems perceive and navigate physical environments. Intello Labs: Intello Labs develops computer vision AI solutions for agricultural quality assessment and food supply chain automation, enabling buyers, processors, and retailers to grade the quality of fresh produce, grains, and perishable goods using smartphone cameras or fixed imaging stations connected to AI analysis models. The platform delivers objective quality measurements that replace subjective visual inspection in procurement, warehouse intake, and retail shelf management.\n\nThe company raised approximately $10M in Series A funding and has deployed its computer vision quality grading systems at agricultural procurement centers, cold chain warehouses, and food retail chains across India. Intello Labs has built proprietary image datasets covering hundreds of agricultural commodities at varying quality grades that serve as training data for its vision models.\n\nFood quality standardization is a persistent challenge in India's agricultural supply chain, with inconsistent grading causing significant economic losses and trade disputes between buyers and sellers. Intello Labs' AI-powered objective quality measurement addresses this market inefficiency with a mobile-accessible solution that does not require specialized hardware or technical expertise to operate.

Intello Labs was founded first in 2016, giving it 8 years of additional market experience. World Labs was founded later in 2024. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Both World Labs and Intello Labs report similar employee counts of approximately 50-200. Team size is often a proxy for operational scale, though lean AI companies can punch well above their headcount.

Yes, World Labs and Intello Labs are direct competitors — both operate in the Computer Vision space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.