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Uber Expands AI Data Platform to Power Next-Gen Enterprise and AI Lab Needs

by Jane Doe
June 20, 2025
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Uber Technologies, Inc. today announced a significant expansion of its AI data services business, Uber AI Solutions, making its advanced technology platform available to support AI labs and enterprises worldwide.

This strategic move aims to accelerate AI development by providing customized data solutions, global digital task networks, and robust tools for building and testing AI models more efficiently.

Leveraging a decade of expertise in collecting, labeling, testing, and localizing data for its expansive global operations – from optimizing search functionalities to training self-driving systems and developing generative AI agents for customer support – Uber is now offering this specialized capability to other businesses.

“We’re bringing together Uber’s platform, people, and AI systems to help other organizations build smarter AI more quickly,” stated Megha Yethadka, GM and Head of Uber AI Solutions. “With today’s updates, we’re scaling our platform globally to meet the growing demand for reliable, real-world AI data.”

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The expanded offerings through Uber AI Solutions, now available in 30 countries, include several key advancements:

  • Global Digital Task Platform: This platform connects enterprises with a global talent pool, including experts in coding, finance, law, science, and linguistics. It facilitates tasks such as annotation, translation, and editing for multi-lingual and multi-modal content, extending Uber’s successful gig-work model into the AI domain.
  • New Data Foundry: A new service providing ready-to-use and custom-collected datasets, encompassing audio, video, image, and text. Built with data ethically sourced by individuals using Uber technology, this foundry supports diverse use cases like generative AI, mapping, and speech recognition, with a strong emphasis on privacy and compliance.
  • Agentic AI Support: Uber AI Solutions is providing the necessary tools and data to train sophisticated AI agents. This includes realistic task flows, high-quality annotations, simulations, and multilingual support, enabling AI agents to better understand and navigate real-world business processes.
  • Shared Infrastructure for AI Builders: Uber is making its internal platforms, which manage large-scale annotation projects and validate AI outputs, accessible to enterprise clients. This includes AI-powered smart onboarding, quality checks, smart task decomposition and routing, and feedback loops to ensure accuracy and efficiency.

This expansion positions Uber AI Solutions as a critical “human intelligence layer” for global AI development, combining software, operational expertise, and massive global scale.

Looking ahead, Uber plans to introduce an AI-powered interface that will allow clients to simply describe their data needs in plain language, with the platform automating setup, task assignment, workflow optimization, and quality management for scalable AI training.

Jane Doe

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