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This research defines the Knowledge Authorization Gate (KAGe) and its role in addressing authorization safety.

July 14, 2026Open Access

KAGe Specification: Definition, Seven Conditions, and Architectural Design

Key Points

This research defines the Knowledge Authorization Gate (KAGe) and its role in addressing authorization safety.
Formally defines KAGe including properties and conditions using Lean 4 with zero sorry stubs.
Identifies seven conditions (C1-C7) essential for the KAGe mechanism.
Implements KAGe in Kuriom to enforce pre-execution knowledge admissibility.
KAGe ensures that decisions based on knowledge are deterministic and recorded immutably.
Seven conditions are verified, confirming their validity for safe authorization.
Kuriom successfully implements KAGe for AI agent sequences, indicated by live system deployment.

Abstract

The Knowledge Authorization Gate (KAGe) is the pre-execution mechanism that closes the Knowledge Authorization Gap (KAG) -- the discrepancy between the evidence required to safely authorize a consequential action and the evidence actually available and governing at the time of authorization. This specification defines the KAGe formally: its definition, three structural properties (pre-execution, deterministic, immutable record), seven conditions (C1-C7), gate decisions, knowledge lifecycle, and relationship to the KAG. Seven conditions are formally verified in Lean 4 with zero sorry stubs (DOI: 10.5281/zenodo.21246407). The KAGe is implemented in Kuriom -- the first working system to enforce pre-execution knowledge admissibility for AI agent sequences. The gate is live at api.kuriom.ai. Related publication: Kuriom-ai/kag-framework-paper: Knowledge Authorization Gate v1.0.1. DOI: 10.5281/zenodo.21315673. Patent Pending: 64/008,411 · 64/043,572 · 64/049,750 · 64/059,101 · 64/095,301 · 64/095,302 · 64/095,303

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