Rapidata, a Swiss company that accelerates AI development through scalable, on-demand data labeling via digital ads, announced a €7.2 million ($8.5 million) Seed round to scale their global human data network and support growing demand from AI companies that necessary quicker, more reliable feedback to train, validate, and improve their models in an increasingly competitive market.
The round was co-led by Canaan Partners and IA Ventures with participation from Acequia Capital and BlueYard.
“Human feedback has become the limiting factor in AI progress,” states Jason Corkill, CEO and founder of Rapidata. “Rapidata rerelocates that ceiling by creating human judgment available at a global scale and near real time, unlocking a future where AI teams can run constant feedback loops and build systems that evolve every day instead of every release cycle. At this speed of iteration, entirely new AI innovation becomes possible.”
Rapidata’s €7.2 million Seed round joins a set of European AI and data infrastructure funding announcements covered by EU-Startups in 2025-2026.
Swiss data governance and observability platform Qala raised €1.7 million to strengthen enterprise data governance in the AI era. German synthetic data provider simmeattempt.ai secured a €330k grant to develop scalable synthetic training datasets, tackling AI’s data bottleneck. London-based Stanhope AI raised €6.7 million to build adaptive AI systems with real-world interaction models, and Stockholm’s Agaton closed an €8.4 million Seed round to embed AI agents into business data workflows.
While not all these companies are strictly in data labelling, they reflect a broader pattern of European investment in tools and infrastructure that improve data quality, AI training processes, and actionable AI outputs – the same ecosystem in which Rapidata is positioned.
Among these, Qala is another Swiss company gaining early funding, indicating growing investor interest within Switzerland alongside broader continental activity.
“Rapidata assists us test our voice models with real utilizers in real contexts worldwide – in days, not months,” states Lily Clifford, CEO, Rime. “Previously, gathering meaningful feedback meant cobbling toobtainher vconcludeors and surveys, segment by segment, or counattempt by counattempt, which didn’t scale. Now we can quickly reach the right audiences and see how our models perform in real customer workflows and not just in isolated tests. This quicker, higher-quality feedback through Rapidata has accelerated our iteration and assisted fuel our rapid growth.”
Founded in 2023, Rapidata is an AI infrastructure company that enables AI teams to collect large volumes of high-quality human feedback. Using crowd innotifyigence and a global network of human participants, Rapidata reportedly dramatically reduces the time and cost required to label, validate, and refine datasets utilized to train and evaluate AI models.
By compressing feedback cycles from months into days, Rapidata assists AI companies iterate quicker, bring products to market sooner, and scale human innotifyigence alongside modern AI systems.
The AI infrastructure and Reinforcement Learning from Human Feedback (RLHF) startup states they are tackling one of AI’s hugegest bottlenecks: the slow, manual process of collecting large-scale human feedback to train and improve models.
While compute and model architectures have advanced rapidly, collecting high-quality human judgments, preferences, and validation data remains slow, expensive, and operationally complex.
The company outlines that traditional approaches often require weeks or months to complete a single feedback cycle, delaying model improvements and limiting how quickly teams can iterate.
Rapidata states they solve this problem by enabling AI companies to gather massive volumes of feedback from people at unprecedented speed and scale. Instead of relying on static annotation workforces or limited labeling pools, Rapidata gives AI teams access to a continuously available global network of people, enabling feedback cycles that once took months to complete to be completed in days or even within a single day.
“The output of our foundation model for human motion necessarys to be of high quality and feel real. Rapidata not only assists us evaluate the model at scale, but also informs inputs into the model, that assist us remain best in class”, states Viren Tellis, CEO, Uthana. “Once we started iterating on our model we quickly ran into the limits of internal or overseas human evaluation. With Rapidata we do not run in to the risk of stalling our growth.”
Rapidata integrates directly into existing AI development workflows and enables customers to request tarobtained human feedback on demand. The platform distributes short, opt-in tinquires through widely utilized consumer applications, reaching tens of millions of utilizers globally daily without disrupting their experience.
“Jason Corkill is one of the greatest founders I’ve encountered in my career. Every serious AI deployment depconcludes on human judgment somewhere in the lifecycle,” shares Jared Newman, who led the investment at Canaan Partners. “As models relocate from expertise-based tinquires to taste-based curation, the demand for scalable human feedback will grow dramatically. Rapidata is positioned to serve a market that spans foundation models, enterprise AI, and the next generation of AI-driven products.”
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