Our robust data labelling, advanced testing frameworks, global scale in creating high-quality, reliable models & end-to-end solutions that drive innovation, streamline operations, and speed up time to market.
Generative AI & LLM labelling
Enterprises trust Uber's AI Solutions to annotate, curate, test, and localise high-quality datasets for robust, scalable Generative AI and large language models.
9+ years
Expertise in managing large-scale AI and ML operations
100+ languages
Including languages in Asia, Europe, Latin America, the Middle East, and more
25+ features
Chat or text summarisation
Consensus labelling
Data collection: audio/video/image
Open-ended text descriptions to image/video/anime
Preference rating for multiple responses
Prompt response evaluation/ranking
Side-by-side review and rating/edits
Synthetic data creation
10+ areas of expertise
Auto
Entertainment
Finance
Gaming
Language
Programming
Reasoning
Science
Sport
TV and movies
Custom AI and ML frameworks for your product
- Define use cases and behaviour
- Ensure readiness through collateral development
- Validate coverage of test cases
- Evaluate model learning capability
- Evaluate response speed, error rate, and time to load responses
- Monitor memory, network usage, and configuration
- Develop A/B testing to validate fluency, contextual awareness, and relevance
- Test decision linearity for response coherence
- Validate accessibility, UI/UX, user engagement, linguistic accuracy, and much more
- Benchmark against other AI/ML products
Use cases
Synthetic data creation
Creating Q&A pairs from scratch across a wide range of topics (like travel and food) or for specific specialised categories (such as programming and finance) and in 100+ languages worldwide.
Open-ended text descriptions to image/video/anime
Supplying text summaries using visual aids for gen AI start-ups that create images, videos, or anime from text prompts, or the other way around.
Data collection: audio/video/image
Different activities, different voices, different acoustic conditions, different regions and genders, and more.
Preference rating for multiple responses
Preference for rating/ranking multiple responses to the same prompt (LLMs or text-to-image/video models)
Consensus labelling
Classification or rating carried out across multiple diverse groups (such as regions and genders) to reach a consensus score and remove bias.
Chat or text summarisation
Providing a summary and/or assessing model output on summarisation.
Side-by-side review and rating/edits
Compare several model responses to a prompt side by side, then rate or edit the responses.
How is Uber different?
Uber | Other | |
|---|---|---|
Expertise in the subject matter | Uber’s team of tech program managers has decades of expertise leading globally scaled operations across our core verticals and apps, including rides, delivery, freight, and AI applications. We use this extensive experience to design solutions and work with our network to make sure your needs are met with precision and efficiency. | Only offer expertise for managing operations. |
Product quality | Our AI/ML product testing framework carries out ongoing evaluations of your product(s) to assess model performance, usability, and functionality. Insights gained from these tests directly inform customer requirements, driving continuous improvements and making sure your product not only meets but also exceeds expectations. | N/A |
Quality of process | We focus on a dynamic, ongoing process that brings feedback from domain experts, evaluators, and experienced SMEs in our network of operators straight into the guidelines, making sure they’re always improving and staying relevant. | Customer gave instructions to deliver datasets. |
Additional investment | We bring in the expertise of SMEs to create thorough style guides that capture cultural nuances, genuine language use, and emotional intelligence. On top of that, we have a skilled partner engineering team to build tech solutions that back up human QA, like plagiarism detection tools. Our eLearning platform provides training for operators around the world, making sure knowledge is shared consistently and stays current. We’re dedicated to setting metrics for process and product evaluation, spotting trends and patterns, and using detailed metric analysis to guide future plans. | Provide only training, policy, and operations data analysis. |