Uber Scaled Solutions for generative AI, LLMs and more
Enabling generative AI companies to accelerate innovation, enhance model precision, and achieve global reach with Uber's data labeling, testing, and localization
Why partner with Uber Scaled Solutions?
Uber’s powerful data labeling, advanced testing frameworks, and global scalability support generative AI companies in creating high-quality, reliable models. With over 8 years of experience and a global network of AI-focused teams, Uber has end-to-end solutions that drive innovation, streamline operations, and accelerate time to market for generative AI applications.
High-precision data for advanced model training
uLabel’s multimodal capabilities provide rich, nuanced data that strengthens generative models and improves accuracy.
Accelerated development and time to market
Streamlined annotation and testing processes shorten development cycles, enabling rapid deployment and scalability.
Enhanced global relevance
Localization expertise makes sure generative models produce contextually accurate outputs catering to diverse cultural and language requirements.
Operational efficiency with reduced costs
Scalable solutions reduce overhead and enable flexible growth, allowing resources to be allocated efficiently.
User-centric testing for high-quality output
Real-world scenario testing ensures that generative applications produce engaging, coherent content, enhancing user satisfaction.
Scalable infrastructure for rapid growth
High-volume task management supports evolving generative AI projects, allowing companies to expand without sacrificing quality.
How this could apply to you
- High-quality data annotation for generative training
Label intricate multimodal data, from tone-specific text to detailed visual styles, to enrich generative AI models.
Impact: Supports faster, more accurate model training for a broad range of creative applications
- Localization and cultural adaptability
Test generative outputs for cultural, linguistic, and contextual relevance, adapting to global markets with ease across 100+ languages.
Impact: Increases user engagement and inclusivity by making sure outputs resonate across diverse audiences
- Complex scenario simulation and testing
Evaluate models in real-world scenarios, from interactive chatbot responses to image generation, ensuring reliability and creative coherence.
Impact: Improves user experience with high-quality, stable outputs that meet real-world demands
- Product testing for scalability and responsiveness
Run comprehensive testing on generative applications for performance under high user load and dynamic content demands.
Impact: Ensures that generative AI apps can scale smoothly and maintain high performance across platforms
How we do this with our tools
- Comprehensive annotation for generative models
uLabel provides intricate tagging for diverse data types—including text, image, audio, and video—ensuring rich data to train generative AI.
- Multimodal and contextual labeling
Handles complex, multilayered data inputs, supporting the nuanced requirements of generative AI across formats and applications.
- Adaptive labeling criteria
Customized annotation parameters allow for specific needs, such as emotional tone for conversational AI, stylistic elements in image generation, and language nuances.
- Quality-controlled annotation
Built-in accuracy checks and AI-assisted validation ensure reliable, error-free labeled data that drives model performance and innovation.
- Scalable task management
uTask coordinates large-scale labeling projects across Uber’s specialized teams, optimizing workflows for speed and quality.
- Skill-based workforce allocation
Assigns tasks, such as sentiment analysis, creative language understanding, and visual style recognition, to annotators with domain-specific expertise.
- Real-time analytics and insights
Provides transparency, showing project progress, quality metrics, and team performance through live dashboards and detailed reporting.
- Flexible, high-volume capability
Designed for rapid scaling, uTask adapts to complex generative AI needs, supporting projects of any size.
- Robust testing for generative applications
uTest simulates real-world user interactions and stress-tests generative models in apps for stability, responsiveness, and creative coherence.
- Localization and cultural adaptability testing
Validates generative outputs across 100+ languages, global cultures, and demographics to ensure high relevance and inclusivity.
- Scenario-based testing
Leverages real data to evaluate performance across use cases like conversational AI, image synthesis, and dynamic content creation.
- AI-driven quality assurance
Detects anomalies and optimizes model performance by using AI insights coupled with Uber’s strategic program managers, thereby reducing risks and ensuring readiness for live deployment.
關於我們
概觀
8 年以上的 精湛專業經驗
超過 30 種功能
超過 100 種語言
解決方案
資料註解與標籤
測試
語言與本地化
產業
汽車與自動駕駛技術
銀行、金融服務和保險業
目錄管理
聊天機器人/客服
消費者 App
電子商務/零售業
生成式 AI
健康/醫療人工智慧
製造業
媒體/娛樂
機器人
社群媒體
科技產業
服務項目
資料標籤
推理
文字和語言
圖片
媒體
搜尋
測試
E2E 功能測試
語言測試
無障礙功能和法規遵循
模型評估
App 效能測試
本地化
產品使用者介面
行銷
客服
法務
技術
uLabel
高度靈活的使用者平台，全面滿足您的數據需求
uTask
完全可配置的即時工作編排平台，可滿足您的所有需求
測試環境
Uber 自訂的測試管理與測試平台
uTranslate
Uber 的內部平台，為全球各地的使用者提供本地化的 App 體驗