Exogram Action
Admissibility Protocol
Identity and Access Management for Non-Human Entities.
A deterministic execution control plane between AI inference and real-world state changes. EAAP ensures no autonomous agent action reaches production without cryptographic verification of admissibility.
Median Compute
Sustained RPS
Architectural Layers
DB Secrets Exposed
“Agents are probabilistic. Infrastructure is deterministic.”
Exogram is the execution control plane between them.
— EAAP Core Thesis
The Problem
An enterprise orchestration framework cannot securely govern its own database writes. The agent cannot act as its own security guard.
When an AI agent proposes a state-changing action — a billing modification, a compliance update, a database write — there must be an independent, deterministic authority that cryptographically verifies the action before it reaches production. Without this boundary, every autonomous agent is a latent insider threat.
Critical Gap
No orchestration framework — LangChain, NemoClaw, CrewAI — provides cryptographic execution gating. They route actions. Exogram governs them.
As AI agents transition from advisory to executive roles in production systems, the gap between probabilistic inference and deterministic execution creates a critical governance void. EAAP proposes a four-layer control plane that evaluates every proposed agent action through ledger governance, semantic retrieval, policy evaluation, and cryptographic execution gating — ensuring that no autonomous action modifies production state without verified admissibility.
The Proxy Model
Exogram operates as a cryptographic proxy between the AI agent and the enterprise database.
AI Agent
Proposes action
Exogram Checkpoint
SHA-256 state hash
Verify → Sign → Commit
Enterprise DB
Rejects if hash missing
The Four Layers
Layer 1
Ledger Governance
Purpose: Enforce ledger integrity
PII scrubbing via deterministic pattern detection, encryption at rest, semantic indexing, conflict detection, confidence scoring, fact locking, and audit event logging.
Layer 2
Meaning Engine
Purpose: Assemble bounded, deterministic context
Namespace isolation, deterministic relevance scoring, temporal decay weighting, conflict surfacing, context health classification, snapshot generation, and HMAC snapshot signing.
Layer 3
Judgment Engine
Purpose: Deterministic admissibility evaluation
Authority validation, fact consistency enforcement, constraint evaluation, confidence threshold enforcement, and escalation classification.
Layer 4
Action Admissibility
Purpose: Guarantee execution integrity
Claim extraction from payload, pre-flight conflict detection, SHA-256 state hashing, evaluation record creation, commit validation, and immutable action ledger.
Evaluation Protocol
State Hash Formula
state_hash = SHA-256(
sorted(relevant_objects) ||
policy_version ||
namespace_id ||
floor(timestamp, window)
)Protocol Invariants
Mandatory and non-configurable. Cannot be weakened without a major version change.
PII Air Gap
No detected PII enters persistent storage or vector embeddings
Encryption at Rest
All content encrypted with per-user Fernet keys before persistence
No Silent Overwrite
Conflicting facts require explicit resolution — never silently replaced
Namespace Isolation
Retrieval and evaluation scoped strictly to user namespace
Immutable Audit Chain
Cryptographically chained audit events — tamper-detectable
Deterministic Judgment
Execution gates use code, not LLM inference
Confidence Decay
Facts degrade in authority over time unless reinforced
State Hash Integrity
Execution requires identical state between evaluation and commit
Evaluation Expiry
Approvals expire after a defined TTL — no stale tokens
Hard Deletion (GDPR)
Full deletion removes vectors, ciphertext, and all associated records
Specification Details
Full Specification
Read the complete EAAP specification with threat model, evaluation protocol, commit guarantees, and security invariants.