Architecture Overview

Separation of cognition (model) and control (kernel).

Control Flow Architecture

User / LLM
(suggests intent)
AegisAI Kernel
+ Policy Engine
← deterministic, auditable, sovereign
(decides outcome)
ALLOW
WARN
CONFIRM
BLOCK
(if allowed)
Tool / Action Execution
(always)
🔒 Audit Trace (SHA-256)

LLM cannot execute actions. Only the Kernel can.

🔐

LLM as Transducer

The model maps natural language to typed intent — nothing more. It produces structured requests but has no capability to execute them.

👑

Kernel Sovereignty

The Kernel is the sole authority for decisions and action gating. It runs deterministic policy evaluation on every request.

📊

Graduated Outcomes

Four possible outcomes: ALLOW (proceed), WARN (proceed + log), REQUIRE_CONFIRM (wait for human), BLOCK (deny).

🔗

Cryptographic Evidence

Every decision generates a SHA-256 hash linked to the previous record. Tamper-evident, forensic replay possible.

Tool Governance ABI v1

ActionRequest

{
  "tool_id": "send_payment",
  "parameters": {...},
  "correlation_id": "ulid",
  "timestamp_utc": "ISO8601"
}

ActionResult

{
  "status": "BLOCKED",
  "reason_code": "FINANCIAL_TX_LIMIT",
  "audit_hash": "sha256:...",
  "correlation_id": "ulid"
}

Architectural Invariants

  • HIGH severity policy violations always result in BLOCK
  • Every tool call requires explicit policy authorization
  • Decision traces are append-only and hash-chained
  • Identical inputs produce identical policy outcomes
  • LLM output is parsed, never executed directly