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Rapidata Raises $8.5 Million to Accelerate AI Development Through Global Crowdsourced Feedback
NewDecoded
3 min read
Image by Rapidata
Rapidata announced an $8.5 million Series Seed round on February 19, 2026, to tackle the critical human bottleneck in AI training. The round was co-led by Canaan Partners and IA Ventures, with participation from Acequia Capital and BlueYard. This investment marks a significant step for the Zurich-based startup as it seeks to redefine how models are aligned with human preferences.
The company, a spinoff from ETH Zurich, provides a platform for Reinforcement Learning from Human Feedback (RLHF) by utilizing digital advertising space. Instead of traditional static labeling workforces, Rapidata distributes micro-tasks through mobile apps and websites globally. This approach allows AI developers to gather millions of human judgments in hours rather than weeks.
Current AI development is often slowed down by the manual process of collecting preference data and validating model outputs. While compute power has scaled rapidly, human validation remains expensive and operationally complex. Rapidata addresses this by treating human attention as a high-velocity cloud resource accessible via a simple API.
The new capital will be used to expand the company's global human data network and enhance its self-serve infrastructure. These improvements aim to support growing demand from foundation model builders and enterprise AI teams. By shortening feedback cycles, the company enables developers to run constant iteration loops for their systems.
Strategic partners like voice AI firm Rime and generative motion developer Uthana are already utilizing the platform for real-world testing. Rime uses the network to test voice models with real users in specific contexts across different countries. This allows them to verify emotional resonance and natural sound quality at a scale previously impossible through traditional surveys.
According to Jason Corkill, the CEO and founder, human judgment is currently the limiting factor in AI progress. The platform aims to remove this ceiling by making human feedback available in near real time. This capability unlocks a future where AI systems can evolve daily instead of waiting for long release cycles. More details on the technology can be found at https://rapidata.ai/.
This funding highlights a major shift in the AI infrastructure stack from raw compute to high-quality data acquisition. As foundation models move beyond simple logic and into the realm of human taste and creative nuance, the need for diverse human input becomes the primary competitive differentiator. Rapidata is effectively commoditizing human judgment, turning subjective feedback into a scalable utility that functions much like on-demand server capacity. For the industry, this means the speed of model alignment will finally catch up to the speed of model training, potentially leading to daily or even real-time updates for complex AI agents.
