Nas web3

The moment has arrived when AI can be rebuilt with fairness at its core. is not just another protocol it is a full stack for community owned AI where data contributors model builders and end users all share in value creation. @OpenLedger is designing an AI blockchain that treats data as first class infrastructure and makes model provenance attribution and real time rewards part of the protocol logic
What is the mission in plain language
Put ownership back into the hands of people who create the signals that train intelligent systems. aims to unlock liquidity in data and models so that contributors receive transparent pay for influence while developers gain access to curated domain datasets and infrastructure to build specialised models and applications. The platform is built to prevent black box value capture and to enable a flourishing open AI economy that is community governed.
How the system is organised at a high level
OpenLedger organises contributions into Datanets which are decentralised collaborative datasets aligned to vertical domains. A Datanet collects contributions metadata and validation logic so a community can curate high quality training corpora for specific use cases. Each Datanet contains attribution metadata so contributors are visible and accountable when their data is used for model training or retrieval. This is where real world domain expertise becomes a monetisable public good.
Proof of Attribution and why it matters
At the heart of the protocol is Proof of Attribution a cryptographic attribution system that links every data contribution to model outputs. This is not marketing language it is a concrete mechanism that enables tokenised rewards based on measured data influence. The protocol records provenance in a way that allows model outputs to show which data items contributed to an inference and to compensate contributors accordingly. That means contributors are rewarded when their data actually moves the model and bad or adversarial inputs can be penalised or down weighted in a transparent fashion. This design solves two fundamental problems attribution and reward for at scale AI systems
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ModelFactory and the no code path to specialised models
ModelFactory is the OpenLedger studio product that removes heavy ops overheads and lets builders fine tune base models using permissioned Datanets via a GUI. The product supports full fine tuning LoRA and QLoRA workflows so teams and individuals with limited infra budgets can create high quality domain models without wrestling with complex pipelines. This opens the door for subject matter experts to turn curated datasets into deployable models in hours rather than weeks. ModelFactory is the on ramp for organisations that need domain performance and traceable provenance.
OpenLoRA and extreme inference efficiency
OpenLoRA is the runtime and deployment layer that focuses on dramatically lowering inference cost and raising density of served models. The platform has documentation and benchmarks showing orders of magnitude reduction in deployment cost so developers can host many specialised models on far fewer GPUs. That efficiency lets small teams and communities offer paid model endpoints and agent services without prohibitive hosting bills. In short OpenLoRA converts model innovation into commercially viable services.

Architecture and interoperability essentials
OpenLedger is architected as a Layer 2 style AI chain optimised for data availability scalability and compatibility with EVM tooling. The design uses modern data availability primitives and ties settlement back to Ethereum so developers can leverage familiar wallets SDKs and existing composability patterns. The result is a stack that balances throughput with economic finality and keeps user experience smooth while preserving decentralized settlement guarantees. This choice makes it easy for existing web3 builders to integrate and for enterprise adopters to reason about risk.
Concrete use cases and examples of impact

$OPEN #OpenLedger