Rapidata, an AI infrastructure startup specializing in scalable Reinforcement Learning from Human Feedback (RLHF), today announced an $8.5 million Series Seed round co-led by Canaan Partners and IA Ventures, with participation from Acequia Capital and BlueYard. The funding addresses one of the most persistent challenges in AI development: the slow and costly process of gathering high-quality, large-scale human feedback essential for training, validating, and refining models.
Human feedback remains a critical limiter in advancing AI models, even as compute power and architectures have progressed rapidly. Traditional methods for collecting preferences, validations, and judgments are manual, expensive, and time-intensive, often delaying iterations and constraining innovation speed. Rapidata eliminates this constraint by creating a continuously available global network of participants who provide targeted, high-quality responses in near real time. This enables AI teams to run constant feedback loops, iterate daily rather than per release cycle, and deploy improved models much faster in a highly competitive landscape.
Rapidata distributes brief, opt-in tasks through popular consumer applications, tapping into diverse global audiences without disrupting user experiences. Over time, the platform develops trust and expertise profiles to match tasks with the most suitable respondents, ensuring consistent data quality at massive scale. Unlike conventional annotation services that rely on fixed workforces, Rapidata offers on-demand access that integrates directly into existing AI pipelines, removing the operational burden of managing custom labeling operations while delivering cost-effective, reliable results.
“Human feedback has become the limiting factor in AI progress,” said Jason Corkill, CEO and founder of Rapidata. “Rapidata removes that ceiling by making 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 helps us test our voice models with real users in real contexts worldwide—in days, not months,” said Lily Clifford, CEO, Rime. “Previously, gathering meaningful feedback meant cobbling together vendors and surveys, segment by segment, or country by country, 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 faster, higher-quality feedback through Rapidata has accelerated our iteration and helped fuel our rapid growth.”
"The output of our foundation model for human motion needs to be of high quality and feel real. Rapidata not only helps us evaluate the model at scale, but also informs inputs into the model, that help us remain best in class”, said 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”
“Jason Corkill is one of the greatest founders I've encountered in my career. Every serious AI deployment depends on human judgment somewhere in the lifecycle,” said Jared Newman, who led the investment at Canaan Partners. “As models move from expertise-based tasks 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.”
With this new capital, Rapidata plans to expand its global human data network and meet the accelerating needs of AI companies seeking faster, more dependable feedback to stay ahead in model development and deployment. The platform's ability to compress timelines and reduce costs positions it as a key enabler for the next phase of AI innovation, where rapid iteration powered by scalable human intelligence becomes essential.
About Rapidata
Rapidata is an AI infrastructure company that enables AI teams to quickly and cost-effectively collect large volumes of high-quality human feedback. Using crowd intelligence and a global network of human participants, Rapidata dramatically reduces the time and cost required to label, validate, and refine datasets used to train and evaluate AI models. By compressing feedback cycles from months into days, Rapidata helps AI companies iterate faster, bring products to market sooner, and scale human intelligence alongside modern AI systems.
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