Aegis Runtime Control for Agentic AI

Put policy in the execution path of AI agents.

Aegis turns policy documents into signed runtime authority, then independently checks AI actions before they touch tools, APIs, workflows, or data systems.

Not a policy chatbot. Not a compliance dashboard. Independent runtime control for agentic AI.
Independent runtime control
Copilot · Salesforce · ServiceNow · Custom Agents Existing AI systems propose actions.
↓ proposed action
AEGIS RUNTIME CONTROL Checks active policy state, trust region, operation map, evidence, scope.
↓ decision
Allow
Escalate
Deny
↓ authorized execution only
Tools · APIs · Workflows · Data Systems Effectful systems are touched only after Aegis authorization.
Evidence chain recorded across ingestion, authority, activation, decision, and outcome.

AI systems are becoming action engines.

Copilot, Salesforce agents, ServiceNow workflows, and custom LLM apps can draft, route, update, call APIs, trigger workflows, and affect real systems. The system proposing an action should not be the only system deciding whether that action is allowed.

Policy as context is not control.

Retrieving a policy into model context may help answer questions, but it still leaves the model as interpreter. The model may receive governed context, but it should not hold authority.

Logging after the fact is not prevention.

Monitoring can tell you what happened. Runtime control decides whether the action is allowed before it reaches APIs, workflows, records, or data systems.

A wrapper changes what the model sees. Aegis controls what the model can do.

Aegis sits between AI intent and enterprise effect.

Aegis does not replace enterprise AI tools. It provides the independent control point between those tools and the systems they affect.

AI & Apps

Microsoft Copilot, Salesforce Agentforce, ServiceNow, internal workflows, custom LLM apps.

Aegis Runtime Control

Validates proposed actions against signed runtime authority before any system is touched.

Systems & Tools

APIs, workflows, data systems, SaaS platforms, records, customer communications.

Not another AI assistant.
Aegis is an enforcement layer, not a chatbot or copilot.
Not a prompt wrapper.
It does not rely on the model's own restraint to enforce policy.
Not self-grading.
The system doing the work is not the only system judging whether the work is allowed.

What happens after you upload a policy?

A policy upload does not become a prompt. It becomes source evidence, then reviewed governance material, then signed runtime authority.

01

Document

Policy, standard, procedure, evidence, or internal control material is uploaded.

02

Source Evidence

Scope, metadata, storage refs, content digest, and source-span chunks are recorded.

03

Candidate Clauses

Obligations, prohibitions, permissions, exceptions, approvals, and action implications are extracted as candidates.

04

Human Review

Only approved clauses can feed the compiler. Rejected or unreviewed clauses cannot become active governance.

05

Legal Graph / Trust Region

The rules are structured, and the operating boundary is defined.

06

Signed Bundle

Governance objects are deterministically packaged, hashed, and signed.

07

Aegis-Verified Authority

Aegis verifies the signed runtime state before activation.

Evidence becomes authority only after review, compilation, signing, and Aegis verification.

Aegis enforces a scoped policy stack, not one flat file.

Baseline is the floor. Organisation policy is the overlay. Department policy is the local operating envelope. The agent or workflow scope becomes the runtime enforcement point.

Platform Baseline Regulation, standards, industry packs
Organisation Overlay Company policies, controls, procedures
Department Overlay Local rules, approvals, exceptions
Agent / Workflow Scope Allowed operations, trust region, runtime HEAD
Aegis-Enforced Runtime Authority Active signed composition of the full stack

Each layer narrows the operating envelope for the layer beneath it. The runtime does not enforce a loose PDF, a summary, or a prompt. It enforces the active signed version of the full scoped stack.

Internal policy can add local requirements, procedures, approval rules, and stricter controls. It should not silently weaken the baseline floor.

For a governed action, the evidence chain can show which baseline, organisation overlay, department overlay, trust region, and runtime HEAD applied.

Agent actions are proposals, not permission.

Aegis verifies the signed runtime HEAD, checks the trust region, maps the operation to active policy authority, and only permits execution when the decision is allow.

Aegis verifies runtime authority

Bundle signatureSigned governance bundle authenticated
Scope bindingTenant, org, department, agent scope matches
Trust region digestBoundary map hash verifies
Meta config digestRuntime governance settings verify
Policy hashPolicy layer state matches signed authority
Runtime HEADActive authority pointer is signed and valid

Aegis routes proposed actions

send_email
Allow if mapped
export_file
Approval required
call_api
Aegis-gated
unmapped action
Non-execution
outside trust region
Block
No signed authority, no mapped operation, no valid trust region, no execution.

Four layers. One runtime control system.

The internal names matter for implementation. The buyer outcome is simple: build authority, enforce authority, reason inside authority, prove the chain.

LAYER 1

Build Authority

Policy evidence becomes reviewed, signed governance.

Internal: Praxis
LAYER 2

Enforce Authority

Proposed actions are checked before execution.

Internal: Aegis Kernel
LAYER 3

Reason Inside Authority

Grey areas stay inside the trust region.

Internal: Civitas
LAYER 4

Prove the Chain

Every stage is recorded as verifiable evidence.

Internal: ILK

Not RAG. Not GRC. Not guardrails.

Most platforms put policy around AI. Aegis puts policy in the execution path.

Approach What it does What Aegis does instead
Document repository Stores policy text Constructs signed runtime authority
RAG Retrieves policy context Builds verified governance objects
GRC platform Tracks controls Enforces at the action boundary
Prompt guardrails Instruct the model Verifies before execution
Logging Records after the fact Controls before action
Human approval flow Does not scale alone Trust regions route decisions
Most platforms put policy around AI. Aegis puts policy in the execution path.

What can you prove later?

For any governed action, the evidence chain can show the policy state, the runtime boundary, the decision path, and the outcome.

The claim is not “the AI was right.” The claim is that the system followed a reviewed, signed, active policy state, and the evidence chain can be inspected.
Active policy stateWhich baseline, organisation overlay, and department overlay applied.
Runtime boundaryWhich trust region and operation mapping controlled the action.
Aegis verificationWhether the runtime HEAD and signed governance package verified.
Judgment pathWhether Civitas or an escalation path was involved.
Decision resultAllow, deny, escalate, withhold, or fail closed.
Evidence ledgerWhat ILK recorded across ingestion, authority, activation, decision, and outcome.

Prove one governed workflow end to end.

Choose one workflow. Upload the relevant policies. Build the governance package. Activate runtime authority. Run allow, deny, escalate, and fail-closed cases. Inspect the evidence chain.

20-minute technical brief · Bring one governed workflow · We show the chain
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