A real-world use case: Monetizing user data and interactions for AI model training via OpenChat
One concrete example is OpenChat, an application built on the OpenLedger platform (launched with its private mainnet). In this setup:
Every user interaction (chats, contributions, prompts, etc.) is logged on-chain using Proof of Attribution.
This creates transparent, verifiable records of who contributed what data.
Users are rewarded in real time with OPEN tokens (or related incentives) for providing high-quality data or interactions.
The collected data feeds into training or improving specialized language models (SLMs) — smaller, focused AI models for things like chatbots, copilots, trading tools, virtual assistants, or industry-specific agents.
Developers and companies can access this curated, attributed data to build better AI without relying on centralized, opaque datasets from big tech.
This solves key problems in AI development:
Lack of transparency in training data
No fair rewards for data contributors
Difficulty proving data provenance
By using the OPEN token, the system creates economic incentives: people earn for contributing valuable data/interactions, while model builders pay via gas fees or direct payments to use the infrastructure. This turns everyday user engagement into monetizable, traceable AI fuel.
This use case has been highlighted in recent ecosystem updates as a way to drive real participation and tie growth directly to on-chain activity.
(As of late 2025/early 2026 data, OpenLedger is still expanding, with partnerships in gaming and other sectors exploring similar AI-data monetization patterns.)
If you're looking into trading or holding OPEN, it's listed on exchanges like Binance and has seen use in DeFi/AI crossover scenarios. Let me know if you'd like more details on price, tokenomics, or comparisons!
#OpenLedger #ProofOfAttribution #learntoearnmay