Backed By
Protocol Labs
CMS Holdings
MH Ventures
CV VC
With Angels From
Meta
Ledger
Apple
From SFT to Agents
Whether you're refining RLHF pipelines, orchestrating multi-step RAG processes, or evaluating advanced agents, Reppo adapts to your workflow—no matter how cutting-edge.
Powering Leading AI Teams with high-quality training data
"We participated in an early pilot with Reppo and were impressed by the approach. The crypto-native incentives show real promise for solving data quality challenges we've struggled with for years."
Product Manager at Protocol Labs
"The pilot gave me a glimpse of what's possible. If Reppo can democratize access to quality contributors like this at scale, it'll level the playing field for independent researchers."
Independent AI Researcher
"Our pilot test showed promising results. The prediction market approach to data quality could be significantly better than traditional labeling if it scales successfully."
ML Engineer at Glasstape
"We tested the early platform and the on-demand model with crypto incentives is exactly what the industry needs. Excited to see this vision come to life at scale."
Founder at YC W25
"The pilot demonstrated real potential to accelerate data collection timelines. If Reppo delivers on this promise, it could transform how teams iterate on training datasets."
Research Lead, AI Safety
"Early tests showed that crypto incentives can attract expert contributors for specialized domains. This approach could unlock quality that traditional platforms can't match."
Director of AI at Protocol Labs
"As a solo developer, I'm excited about what Reppo is building. The pilot showed real potential to democratize access to quality training data without vendor lock-in."
Independent Developer
"Our team tested Reppo during early trials for reinforcement learning data. The quality of human feedback exceeded our expectations and the turnaround time was impressive."
Senior Research Scientist, Language Models
"The early pilot revealed an innovative approach to preference data. If this scales as intended, it could significantly reduce the cost and complexity of RLHF workflows."
VP of Engineering at Glasstape
"We explored Reppo's platform for multimodal annotation needs. The crypto incentive model attracted contributors with genuine domain expertise - something traditional platforms struggle with."
Head of Data Science, Autonomous Systems
"During our pilot, we saw how prediction markets can self-correct for quality. This mechanism could be revolutionary for alignment research if it maintains accuracy at scale."
Research Engineer at YC W25
"The early tests showed promising results for complex reasoning tasks. Having access to quality annotators without lengthy vendor contracts could accelerate our model iterations significantly."
Lead ML Engineer, NLP Research