Neura is an agent artifact platform for comparing raw 0G Compute answers with artifact-grounded answers backed by 0G Storage.
Neura is a decentralized knowledge artifact platform for improving specialized AI agents after deployment. When an agent makes a domain-specific mistake, Neura helps turn the correction into a reusable, versioned artifact that other agents can install and use as grounded context.
The current demo focuses on Excel Q&A. Users can compare a raw model answer against an artifact-backed answer powered by curated markdown knowledge packs containing formulas, explanations, edge cases, and benchmark data. This shows how structured artifacts can improve reliability over base model responses alone.
Neura integrates with 0G by using 0G Chain for an on-chain ArtifactRegistry, where artifact IDs, creators, versions, metadata hashes, and storage references are recorded. It also supports 0G Storage for artifact persistence and a 0G Compute-compatible model flow for raw versus artifact-grounded benchmarking.
In short, Neura turns expert corrections into verifiable, reusable infrastructure for better AI agents.
Neura currently provides the artifact layer and benchmarking workflow for improving agents. It does not yet ship a full tool-using agent; that would be the next phase built on top of the artifact system.