Toptal Launched ExpertCrowd Platform for AI Training
The platform leverages a network of PhD-level specialists to scale reinforcement learning and model evaluation.
Updated on Oct. 13, 2026 in Artificial Intelligence
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Toptal has officially launched ExpertCrowd, a platform designed to facilitate AI model training through human feedback and data labeling. The service, which generated $5 million in recurring revenue during its pre-launch phase, provides access to a massive global network of domain experts.
Why it matters
As frontier AI models grow in complexity, developers increasingly require specialized human expertise to improve performance on nuanced tasks. This platform bridges that gap by connecting technical teams directly with PhD-level researchers and data specialists.
The new ExpertCrowd-SWE benchmark evaluates AI coding agents across 87 distinct codebases and 11 programming languages. This testing framework relies on a pool of 1,000 PhD-level AI specialists within Toptal's broader 30,000-person domain expert network.
The players
Toptal
A global talent network that connects enterprises with software engineers, designers, and AI specialists.
ExpertCrowd
A newly launched platform for managing AI model training, RLHF processes, and coding agent benchmarks.
The details
ExpertCrowd functions by utilizing an AI-driven sourcing engine that matches specific domain experts to client projects based on technical requirements. The platform integrates multimodal annotation—the process of labeling different types of data like text, images, and code for training—and live project tracking to support Reinforcement Learning from Human Feedback (RLHF), a method used to align model outputs with human preferences.
Timeline
Toptal was founded in 2010.
Toptal launched the ExpertCrowd platform on October 14, 2026.
The Tech Race
The introduction of the ExpertCrowd-SWE benchmark signals an intensified focus on evaluating AI coding agents against real-world software repositories. This effort aligns with industry-wide attempts to standardize how model performance is measured across diverse programming languages and complex coding tasks.
Enterprise developers and data science teams can immediately access the platform to scale their model training and evaluation workflows. The service provides a direct pipeline for human-in-the-loop validation, though specific availability for independent developers remains unannounced.
The takeaway
ExpertCrowd highlights the pivot toward human-specialized data as the bottleneck for advanced AI model training. Watch for new performance results from the ExpertCrowd-SWE benchmark to see how these human-labeled datasets impact the success rate of autonomous coding agents.
Further reading
For more on the methodologies shaping the next generation of model development, visit Artificial Intelligence.
More information
To explore the network or view service options, visit the Toptal talent network homepage.
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Do you trust that human expert oversight makes artificial intelligence safer and more capable?
