Raiinmaker has officially partnered with SINT to provide human validation to decentralized AI systems. The platform, TRAIIN, is a pilot rollout that enables verified input from humans to increase the reliability and scalability of autonomous agents. The strategic intent behind this move is to get rid of control through artificial intelligence (AI) in favor of the distribution of power and the establishment of user-centered ecosystems.

🚨 Partnership Announcement

SINT X RAIINMAKER 🤝

We’re joining forces with @sinthive to accelerate the decentralized intelligence revolution.

Where AI, Web3, Metaverse & Robotics converge—Raiinmaker brings human validation to the neural fabric of tomorrow.

SINT is now part of… pic.twitter.com/pUW0clTdFb

— Raiinmaker (@Raiinmakerapp) June 6, 2025

The partnership aims to support intelligent agents to operate efficiently in Web3, robotics and metaverse applications by combining SINT’s AI agent development capabilities with Raiinmaker’s validation infrastructure.

Decentralized and Autonomous Intelligence Infrastructure

This partnership will use the TRAIIN platform as its technical base. This gives AI agents access to a safe layer of human-validated data on which they can make rules and take action based on real world awareness. This structure also prevents agents from relying entirely on the output of their algorithms and instead requires human feedback in the decision-making process.

The support for integration offers large, adaptive, intelligent systems that work at scales exceeding our current protocol constraints. This platform will link to SINT’s AI tools, giving developers a framework to build and test AI agents, with human validation being key in such environments.

Creating Scalable and Transparent Digital Interactions

The two companies share a value in making AI experiences transparent and inclusive. Their approach eliminates traditional gatekeepers and enables users to participate in the development of AI systems. Together, these produce a more secure, trustworthy environment in which digital agents can carry out their work throughout the various decentralized ecosystems.

This collaboration takes a step towards creating autonomous AI models that are grounded in human input. By integrating the pilot, the future of decentralized platforms will be informed.



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