2. Motivation & Problem Statement

Large Language Models (LLMs) are powerful tools for generating content, analyzing data, and making decisions based on human input. However, in their current form, they operate entirely off-chain, with no native way to verify the integrity of their outputs in decentralized environments.

This introduces multiple issues:

Lack of verifiability — Anyone can claim “the AI said this,” but there’s no cryptographic proof.
No audit trail — Outputs can't be linked back to a specific trusted node or signature.
Incompatible with smart contracts — Smart contracts require deterministic, provable inputs. Raw AI responses are neither.
No accountability — Without on-chain attestation, outputs can be spoofed, tampered with, or used out of context.

Osirium solves this by transforming off-chain AI inference into verifiable, EVM-compatible attestations — making AI outputs trustless, traceable, and usable within decentralized applications.

Previous1. Introduction Next3. Architecture Overview

Last updated 14 days ago

2. Motivation & Problem Statement

This introduces multiple issues:

Lack of verifiability — Anyone can claim “the AI said this,” but there’s no cryptographic proof.
No audit trail — Outputs can't be linked back to a specific trusted node or signature.
Incompatible with smart contracts — Smart contracts require deterministic, provable inputs. Raw AI responses are neither.
No accountability — Without on-chain attestation, outputs can be spoofed, tampered with, or used out of context.

Osirium solves this by transforming off-chain AI inference into verifiable, EVM-compatible attestations — making AI outputs trustless, traceable, and usable within decentralized applications.

Previous1. Introduction Next3. Architecture Overview

Last updated 14 days ago