GOVERNANCE INFRASTRUCTURE FOR AGENTIC AI
The Missing Layer Between Your AI and Accountability
Speculum AI governs decisions at boundaries — before, during, and after execution — and generates regulator-grade evidence by default.
Enforce compliance at the decision boundary — not after the incident.
THE PROBLEM
The Accountability Gap
As AI systems evolve into multi-agent decision networks, accountability no longer maps cleanly to a single model, team, or control. In regulated environments, this creates a structural failure point.
Opaque Decision Chains
Multiple agents contribute to a single outcome, without a unified, inspectable reasoning trail.
Attribution Breakdown
When incidents occur, institutions cannot reliably determine which decision, agent, or control failed — or why.
Regulatory Exposure
Supervisors require traceability, justification, and evidence. Agentic systems provide none by default.
Regulatory Reality
“The system decided” is not an acceptable explanation. Accountability must be explicit, attributable, and auditable.
THE SOLUTION
Introducing Mirror OS
Governance infrastructure for agentic AI — adopt it as a full institutional trust layer, or deploy individual components module-by-module. Mirror OS does not replace your models or agents — it restores accountability by embedding governance into autonomous decision flows.
Mirror Trust Layer
Full Governance Proxy for Regulated & Mission-Critical Deployments
Governs autonomous decisions end-to-end and generates audit-ready evidence by default. For banks, government, and regulated enterprises deploying agentic AI in production — where 0.1% failure is not acceptable.
- Boundary policy enforcement
- Governed orchestration across systems
- Regulator-grade evidence and accountability
Deploy Individual Components(Builders & AI Teams)
Start with the exact layer you need — integrate in weeks, expand over time.
Mirror Guard
Decision Interception Layer
Enforces real-time regulatory and policy constraints. Prevents non-compliant actions before execution through enforced control, not just review.
- Input validation & output filtering
- Policy enforcement at I/O boundary
- Prompt injection protection
Mirror Gateway
Governed Orchestration Layer
Coordinates multi-agent interactions within approved workflows. Ensures autonomy operates within institutional boundaries, even at scale.
- Model routing & cost governance
- Quality threshold enforcement
- Multi-agent coordination
Mirror Memory
Reasoning Continuity Layer
Stabilizes multi-step reasoning chains so governance doesn't kill intelligence. Preserves anchors, context integrity, and rollback points.
- Reasoning anchor preservation
- Context stability across handoffs
- Rollback point management
Mirror Ledger Engine
Evidence & Trust Recording Engine
A foundational engine that records, seals, and packages decision evidence — invoked by other Mirror components to ensure auditability, attribution, and long-term trust.
- Tamper-resistant evidence packaging
- Regulator- and court-ready artifacts
- Decision lineage & attribution
ARCHITECTURE OVERVIEW
Mirror OS—The Governance Layer—
Sitting between AI systems and enterprise applications, governance, evidence, and control are enforced at every decision point.
Governance Infrastructure
A product-based governance platform — five components working together to deliver institutional-grade AI governance.
Mirror Trust Layer
Institutional Governance — Policy Enforcement & Risk Containment
Mirror Guard
I/O Control
Mirror Gateway
Governed Orchestration
Mirror Memory
Reasoning Continuity
Mirror Ledger Engine
Evidence Layer
Zero Model Lock-In
<10ms Latency
100% Coverage
Audit-Ready Evidence
Regulator-Grade Trails
Full Attribution
No unmanaged autonomous actions
Governance without operational drag
Freedom without loss of control
Mirror OS does not optimize AI systems. It defines how institutions remain accountable while scaling autonomy.