Product / Federated AI Governance Engine

Federated AI Governance Engine

Sovereign, explainable, and policy-aligned AI execution within your own infrastructure — with zero data egress and full regulatory accountability.

The Federated AI Governance Engine enables banks, ministries, operators, and enterprises to deploy AI-driven decisioning while maintaining complete control over data, models, explainability, and compliance. It transforms AI from a black box into a governed, auditable decision layer aligned with institutional and regulatory requirements.

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Sovereign AI with zero data egress

Explainable, policy-aligned outputs

Deterministic, regulator-ready governance

Runs in VPC, on-prem, or air-gapped

Executive Overview

The Federated AI Governance Engine lets institutions run AI models inside their own perimeter while ensuring zero data egress, full explainability, deterministic policy alignment, and verifiable governance.

AI becomes an augmentation layer to identity, risk, and compliance—not an opaque scoring system. The engine integrates with the Zekret Identity Engine, Attestation & Policy Engine, Screening & Risk Intelligence, and the Deterministic Enforcement Layer for safe, compliant, sovereign AI decisioning across critical workflows.

Local AI execution with no data leaving your perimeter

Explainable outputs aligned to policy and compliance

Federated AI augments identity, risk, and enforcement

Verifiable governance across the full decision lifecycle

What It Solves

Untrusted, opaque AI systems that fail audits

Data privacy barriers to sharing models or inputs

Opaque risk scoring without defensible explanations

Fragmented AI governance across departments/operators

AI Act, NIST, and sector compliance pressure

Core Capabilities

Federated Local Inference

  • Models run inside customer compute (VPC, on-prem, air-gapped)
  • Zekret never accesses data, parameters, or results

Explainability & Transparency

  • Every inference produces reasoning trace and contributing factors
  • Regulator-ready, machine-readable justifications (EU AI Act aligned)

Risk-Aware Augmentation

  • Contextualizes outputs with attestations, compliance rules, and risk signals
  • Prevents AI from violating AML, eligibility, or sector constraints

Policy-Aligned Governance

  • Defines model usage constraints, decision boundaries, and enforcement integration
  • Immutable, version-controlled governance for auditability

Secure Model Lifecycle

  • Model onboarding, versioning, approvals, drift detection, and periodic review
  • Every inference links to model version, policy version, and justification

AI-Augmented Enforcement

  • Feeds behavioral insights and anomaly flags into enforcement
  • AI supplements policy logic; it never overrides it

How It Works

1

Step 1 — Deploy Inside Perimeter

Models run on-prem, in private cloud VPCs, or air-gapped secure compute.

2

Step 2 — Input Normalization

Identity, attestation, and risk inputs are structured without exposing PII.

3

Step 3 — Federated Inference

Models execute locally, generating predictions or insights.

4

Step 4 — Explainability Generation

Each inference outputs reasoning trace, feature contributions, and compliance justification.

5

Step 5 — Policy-Aligned Decisioning

AI outputs feed Attestation & Policy Engine for deterministic constraints.

6

Step 6 — Enforcement

Deterministic Enforcement Layer applies final decisions.

Architecture Overview

Core Components

  • Federated Inference Engine
  • Explainability & Trace Generator
  • Model Governance Module
  • Policy Constraint Enforcer
  • Drift Detection & Monitoring
  • Local Execution Environment
  • Compliance-State Augmentation Layer

Security Architecture

  • Zero data egress; full isolation of model execution
  • No remote access to inference results
  • Immutable governance logs with integrity validation
  • Cryptographic protections across data flows

Data Flow Properties

  • PII never leaves client systems
  • AI uses structured, compliance-aligned inputs
  • Outputs flow into deterministic decisioning pipelines

Deployment Models

Deploy the way you need

Choose the hosting model that aligns with your compliance, sovereignty, and operational requirements.

Private Cloud / VPC

  • Ideal for financial institutions, enterprises, and operators requiring strong boundaries.

On-Premise Deployment

  • For governments, regulators, and critical infrastructure.

Air-Gapped Mode

  • Inference in isolated environments with controlled model update pathways.

Hybrid Sovereign Deployment

  • Split governance and inference layers across secure zones.

Integrations

Upstream Inputs

  • Zekret Identity Engine
  • Attestation & Policy Engine
  • Screening & Risk Intelligence

Downstream Outputs

  • Deterministic Enforcement Layer
  • Case management systems
  • Government eligibility engines
  • Compliance oversight dashboards
  • Responsible gaming systems
  • Transaction or access gating systems

API & SDK Capabilities

  • Model invocation
  • Explainability retrieval
  • Policy-constrained inference
  • Governance logs access

Compliance Alignment

EU AI Act (high-risk requirements)

NIST AI Risk Management Framework

Financial sector model governance

Public-sector explainability obligations

Responsible gaming AI usage constraints

AML/CFT risk governance

GDPR minimal-data principles

Key Benefits

Full AI sovereignty; models run inside your infrastructure

No data egress or exposure of sensitive information

Explainable, regulator-ready AI outputs

AI constrained by policy; no free-form heuristics

Deterministic, auditable decisions

Reduces compliance risk in AI deployment

Enables safe AI augmentation across high-assurance sectors

Integrates with Zekret identity and compliance stack

Deploy AI You Can Trust, Govern, and Defend

Bring explainable, policy-aligned AI into your critical workflows with complete sovereignty.

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