Rapidata

The page explains how to filter annotators using qualification examples before assigning tasks, then reuse trained annotators across jobs.

Rapidata supports up to 100,000 human responses per hour for criteria like naturalness, aesthetics, and cultural fit that reward models cannot assess.

Rank generative-model checkpoints with Bradley-Terry scores from millions of real human comparisons on aesthetics, coherence and prompt alignment.

Humans in the training loop, not a reward model imitating them. Stream policy rollouts to real human raters with TTL-bounded batches that never block training.

The page compares a vision-language model (VLM) with human responses on 325 pairs of pet images.

AI images used to give themselves away through mistakes. The best models have stopped making them. People can still tell, but not the way they used to.

Online RLHF for image and video models usually relies on a learned reward model as a stand-in for human judgement. This post shows how Rapidata Flows bring real human preferences into the post-training loop instead, fast enough to keep up with training and in just a few lines of code.

Research papers that train, evaluate and benchmark models on human feedback collected with Rapidata, from reward models to AI-image detection.

Rapidata announces $8.5M Series Seed co-led by Canaan Partners and IA Ventures to scale its high-quality human feedback platform.

Join Rapidata as AI Platform Engineer (Full-time, Zürich, Switzerland or Bay Area, USA) and build the API to human intelligence that AI teams use for RLHF and evals.

Join Rapidata and help build the interconnect between artificial and human intelligence. View open positions in Zürich.

Join Rapidata as GTM Lead (Full-time, San Francisco, CA) and build the API to human intelligence that AI teams use for RLHF and evals.

Join Rapidata as Motivated Talent 🦄 (Full-time, Zürich, Switzerland) and build the API to human intelligence that AI teams use for RLHF and evals.

Rapidata provides $20 in free credit with no card required, then charges $4 per 1,000 human responses or offers custom pricing for larger volumes.

The page compares Prolific’s hourly-paid crowdworkers with Rapidata’s ad-reached annotators on accuracy, speed, and cost for 300 shared questions.

The page introduces the team behind Rapidata, focusing on crowd intelligence delivered via API.

Rapidata offers up to $50,000 in annotation credits per research project for human judgment on images, video, audio, or text.

For questions or other inquiries, get in touch. Email info@rapidata.ai or book a 30-minute call.

Crowd-intelligence labeling and evaluation. Real human feedback for model evaluation, RLHF, and dataset annotation, in days instead of months.

The page describes Rapidata’s data collection, usage, and safeguarding practices, aligned with EU GDPR, Swiss DPA, and revDPA.

The page outlines the terms governing use of rapidata.ai and its services for customers and partners.

Zurich-based startup **Rapidata** secures **$8.5 million in seed funding** to accelerate human feedback collection for AI training pipelines. The company develops infrastructure solutions that streamline the integration of human input into AI model development, addressing a key bottleneck in scaling generative AI systems. Rapidata’s platform aims to improve efficiency for developers building large language models and other AI applications requiring curated human evaluation.

Feb 2026Crowdfund InsiderNews article

Rapidata secures $8.5 million in seed funding to expand its on-demand human feedback system, accelerating AI model iteration for developers and teams. The platform leverages human input to refine AI training cycles, addressing a critical bottleneck in machine learning workflows. Investors back the approach as a scalable solution for improving model performance without manual intervention.

Feb 2026AI WorldNews article

Rapidata launches a platform that accelerates AI model development by enabling near real-time Reinforcement Learning from Human Feedback (RLHF). The tool reduces training cycles from months to days, targeting developers and enterprises building custom AI applications. The company positions itself as a solution for iterative model refinement and deployment.

Feb 2026VentureBeatNews article

Zurich-based **Rapidata** secures **$8.5 million in seed funding** from investors including **Canaan Partners, IA Ventures, Acequia Capital, and BlueYard**. The capital will accelerate its platform for gathering **human feedback** to improve AI model training and evaluation. The company specializes in scaling real-world data collection for AI development.

Feb 2026zurich.techNews article