Products

Audit Universe

6 specialized AI agents + 4 Knowledge Packs — reproducible, traceable, fail-closed audit operations. Transform manual audit judgment into structured, evidence-backed decision pipelines. POC-ready from day one.

AUDIT UNIVERSEARCHITECTURE

Reproducible Judgment, Not Reproducible Work

6 specialized agents + 4 Knowledge Packs orchestrated through 4-stage audit gates. Every conclusion is traceable to evidence, every judgment is reproducible, and every action is immutably recorded. POC-ready from day one.

Knowledge Packs

Manual Pack

Audit standards, procedures, checklists

Program Pack

Engagement scope, timeline, risk map

Criteria Pack

Assertions, thresholds, regulations

Scope Pack

Boundaries, materiality, sampling

Agent Pipeline
Evidence CollectorFinding AnalystRisk AssessorReport DrafterQuality ReviewerTrace Auditor
Audit Gates
Schema GatePre-Alignment GateExecution GatePost-Audit Gate

Audit Artifacts

Finding ReportEvidence BundleRisk MatrixAudit Trail

Immutable Trace

Every judgment → Evidence snapshot → Full reproducibility

Packs define the standard. Agents execute the judgment. Gates ensure the trace. Evidence proves the conclusion.

AUDIT UNIVERSEWHY NOW

Audit Hasn't Changed in 30 Years. AI Governance Changes Everything.

Traditional audit processes rely on manual effort, subjective judgment, and after-the-fact documentation. MARIA OS replaces this with structured, traceable, reproducible audit operations.

Traditional Audit
MARIA OS Solution

Manual evidence collection across siloed systems

Automated evidence gathering with chain of custody

Subjective judgment with no reproducibility

Structured judgment pipelines with full trace

Findings reports written after the fact

Real-time finding generation during execution

Audit trail gaps and missing documentation

Immutable audit trail by architecture

Compliance mapping requires manual cross-reference

Automated framework-to-control mapping

Quality depends on individual auditor skill

Consistent quality enforced by gates

The question is not whether to use AI in audit. It is how to make AI audit-safe.

Universe Builder

Build Your Audit Universe.

Build Your Audit Universe.

Scope
Evidence
Criteria
Trace
Report
Escalation
Audit Chief
01
Objective
Define audit goal
02
Boundary
Set scope perimeter
03
Agents
Assign 6 specialists
04
Trace Gates
Configure gates 0-3
05
Packs
Load audit knowledge
06
Build
Assemble zone graph
07
Verify
Reproduce checks
08
Deploy
Zone is live

One zone. Six agents. Every trace reproducible.

AUDIT UNIVERSE — AGENTS & GATES

Every Finding Has an Auditor. Every Trace Has a Seal.

Six agents ensure compliance and traceability. Four gates enforce structural accountability.

Evidence Collector

Source identification and evidence gathering

Document ScanSamplingHash VerifyChain of Custody
Finding Analyst

Deviation detection and root cause analysis

Gap AnalysisRoot CauseMaterialityClassification
Risk Assessor

Risk scoring and impact evaluation

Risk MatrixImpact ScoreLikelihoodTrend Analysis
Report Drafter

Finding narrative with mandatory citations

Draft ReportCitation LinkTone AlignTemplate Select
Quality Reviewer

Peer review and completeness verification

Peer ReviewCoverage CheckConsistencyStandards Match
Trace Auditor

Execution trace integrity and reproducibility

Trace VerifyReplay TestTamper DetectAudit Seal
AEvidence Integrity
BJudgment Quality
CRisk Assessment
DReproducibility
Schema Gate

Trigger: Judgment structure not audit-ready

Action: BLOCK

Pre-Alignment Gate

Trigger: Policy/permissions not frozen

Action: FREEZE_THEN_PROCEED

Execution Gate

Trigger: Untracked AI/tool call detected

Action: BLOCK

Post-Audit Gate

Trigger: Explainability or evidence incomplete

Action: REQUIRE_REMEDIATION

Unexplainable judgments are not flagged. They are structurally blocked from execution.

Multi-Agent Team Architecture

Coordinated agents, governed execution

Coordinator, Expert, Metrics, and Repository agents form governed teams — every interaction is enveloped and traceable.

Coordinator
Expert
Metrics
Expert
Repository Layer (LOR)
All dispatches enveloped
Coordinator AgentG1.U*.P0.Z0.A0
Orchestrates task distribution, manages inter-agent communication, and enforces execution order
Expert AgentG1.U*.P*.Z*.A*
Domain-specialized execution — audit rules, sales logic, compliance checks
Metrics AgentG1.U*.P0.Z0.A1
Collects performance data, governance KPIs, and health signals from all active agents
Repository AgentG1.U*.P*.Z*.A-repo
Manages LOR (Local Object Repository) access — evidence storage, policy snapshots, audit trails
Coordination Patterns
Hub-SpokeCoordinator dispatches to specialized agentsUse: Standard universe operations
MeshAgents communicate peer-to-peer with envelope passingUse: Cross-universe chain operations
HierarchicalGalaxy → Universe → Planet → Zone → Agent cascadeUse: Enterprise-wide governance propagation
Governance Overlay
Every dispatch is Enveloped
Agent roles bound to MARIA coordinates
Metrics feed Mission Control in real-time
Repository agents enforce evidence integrity
Agent Teams are not autonomous clusters.
They are governed operating units.
Parallel Audit, Converged Evidence

All audit agents work simultaneously. Evidence converges at the gate.

Chief MARIA orchestrates. Quality loops never stop.

Scope Agent
Scope Boundary
12 controls
Evidence Collector
Evidence Bundle
48 items
Criteria Evaluator
Assessment
Pass/Fail
Trace Recorder
Audit Trail
128 entries
Audit Gate Convergence
All evidence validated before merge
Unified Audit Finding
Scoped, evidenced, evaluated, traced
4
Parallel Evaluations
48
Evidence Locked
100%
Reproducibility Rate
0
Trace Gaps

Parallel evaluation. Full trace. Zero gaps.

AUDIT GATES

4 Gates. Zero Exceptions Without Explanation.

MARIA OS is designed for audit from the start. Every judgment passes through structured gates that ensure explainability and accountability.

Gate 0Schema Gate

Blocks execution if judgment structure is not audit-ready

Unexplainable judgments are structurally blocked from execution.

Decision Envelope & Audit Pack

Every judgment is sealed and auditable

Decisions are wrapped in cryptographic Envelopes — reproducible, verifiable, tamper-evident.

Sealed Envelope
Input Context
Evidence Bundle
Policy Snapshot
Gate Eval Log
AI Model Trace
sha256:9f3a…c71d
Cryptographic Decision Envelope
Input ContextRequest parameters, triggering conditions, and execution scope
Evidence BundleAttached proof documents, data snapshots, and external references
Policy SnapshotFrozen governance rules at the moment of decision
Gate Evaluation LogFull trace of which gates passed, blocked, or escalated
Signature & HashCryptographic integrity — tamper detection guaranteed
AI Model InfoModel version, parameters, and confidence scores recorded
Audit Pack Output (.zip)
Envelope body (JSON)
Event log (NDJSON)
Gate bundle
Policy snapshot
AI trace
Evidence index
Hash manifest
Signatures
Auditor Capabilities
ReproducibleRe-execute any decision with identical inputs and policy state
VerifiableThird-party auditors can independently validate every step
Tamper-EvidentHash chain detects any post-hoc modification
AI decisions are never black boxes.
Audit Deep Dive / Evidence Architecture

Offline Knowledge Pack: 5-Layer Evidence Structure

For government and financial institutions. Knowledge structure prioritizing reliability and explainability over speed.

Layer 01Package Metadata Layer

Who created this knowledge, when, and for what scope

package_idmunicipal-compliance-jp
version1.0.0
scopeLocal Gov Internal Affairs
time_basisAs of April 2025

Distinguishes official government views from operational practices

By separating knowledge origin from interpreter, we ensure audit accountability.

Audit Deep Dive / Gate Policy

Gate Policy: Pre / Decision / Post

In finance, mistakes cause immediate incidents and retroactive fixes are impossible. Knowledge alone is insufficient; Gate Policy integration is essential.

Pre-GateInput Validation

Block before AI touches it

Financial product classification unknown
Immediate Block
Customer attributes undetermined
Immediate Block
Legal basis insufficient
Immediate Block
No matching Evidence in offline knowledge
Immediate Block

Point:If stopped here, AI is never involved at all

Offline Knowledge Referenced by Gate Policy

Knowledge Pack Version
Evidence Presence
Interpretation Risk Rating
Expiration Date

Outdated knowledge, weak basis, high risk → Gate closes

Using AI, but not delegating to AI.

Audit Deep Dive / Risk Level Gates

Risk Level Gate Definition: Level 0-3

Risk levels are defined by responsibility and impact scope, not technical risk. Gates determine where to stop, not accuracy.

Level 0Information Reference
Legal text searchInternal policy lookupTerm definition
Open
Decision MakerHuman
AI RoleSearch & Present Only
Pre-GateKnowledge Pack Verification
Decision-GateAlways Open
Post-GateNo Output Restrictions
Human ReviewNot Required

Point:AI makes no judgments. Digital replacement for paper law books.

Rules Common to All Levels

Immediate block if offline knowledge does not exist
Online information cannot be treated as Evidence
Knowledge pack version is locked in decision log
Decisions that cannot be reproduced later are prohibited

In financial audits, the question is not whether you use AI, but how you stop AI.

AUDIT UNIVERSE — COMPLIANCE MAPPING

Built for Compliance. Not Retrofitted.

MARIA OS maps directly to the controls your auditors already check.

MARIA OS Capability
SOC 2 Type II
ISO 27001:2022
J-SOX
ISAE 3402
Immutable Audit Trail
CC7.2
A.12.4
IT Controls
Control Obj.
Evidence Chain of Custody
CC6.1
A.8.1
Documentation
Testing
Automated Risk Assessment
CC3.2
A.8.8
Risk Assessment
Risk
Responsibility Gates
CC6.3
A.5.3
Segregation
Authorization
Reproducible Judgment
CC7.4
A.12.7
IT Audit
Monitoring

Compliance is not a feature. It is the architecture.

Human-AI Trust Architecture

Intervention is formula, not feeling

When should humans intervene? The answer is a defined equation, not intuition.

Intervention Score
S = Σ wi · xi
Risk Levelw₁ × risk
MVV Deviationw₂ × mvv_dev
Irreversibilityw₃ × irreversibility
PII Exposurew₄ × pii_weight
Uncertaintyw₅ × uncertainty
Gate Threshold Matrix
0 – 0.3AUTO_APPROVEAutomated execution
0.3 – 0.6EXEC_REVIEWManager approval required
0.6 – 0.8BOARD_REQUIREDBoard-level decision
0.8 – 1.0BLOCKExecution prohibited
if pii && external_exposureHUMAN_REVIEW (override)
Rule-Based FirstML is phase 2. Explainable rules come first.
Human Roles DefinedAI and humans don't compete — roles are specified.
Envelope LoggedEvery intervention event is immutably recorded.
Ethics > EfficiencyRejection DAG ensures values override speed.
Judgment Phase vs Responsibility Phase

Separating what to decide from who decides.

Many AI systems blend thinking, deciding, and executing into one. MARIA OS separates judgment from responsibility assignment by design.

Judgment Phase
Compare options
Evaluate against criteria
Place tentative conclusion

AI can assist with judgment. But judgment alone does not authorize action.

RESPONSIBILITY GATE
Responsibility Phase
Confirm who owns the decision
Define scope of accountability
Lock evidence and proceed

Responsibility must be explicitly assigned before execution begins.

AI decides freely. Humans take responsibility blindly.MARIA OS prevents this by structure.

Universe Gate View

3 zones, 3 gates, continuous monitoring

AI operations are visualized as space, not logs. See where agents are, which gates they passed, and where judgments are held.

Finance Zone
3 agents
Operations Zone
2 agents
Compliance Zone
4 agents
Zone
Agent
Gate
Agents cannot freely cross zones
Every boundary requires gate verification
Trace flow is visible at a glance
Adaptive Governance Engine

Self-evolving, but never uncontrolled

DAG updates are governance subjects. Every adaptation passes through Envelope, Gate, and Audit Pack.

01
Detect
02
Propose
03
Gate
04
Apply
05
Audit
Adaptive Proposal Envelope
before_dag_hash: sha256:a3f2...
after_dag_hash: sha256:c8d1...
change_diff: +node(price_adjust)
external_signal_refs: [market_api_v2]
expected_gain: throughput +15%
rollback_strategy: revert_to_prev_hash
g_adaptive_update Gate
irreversibility_check: PASS
impact_universe_scope: sales_only
mvv_deviation: 0.12 (threshold: 0.3)
rollback_possible: TRUE
→ verdict: AUTO_APPROVE
medianAdaptive Reaction TimeChange detection → update applied
98.2%Update Success RateApproved updates without rollback
100%Rollback SafetyAll updates reversible within SLA
12.4%Gate Block RateUnsafe proposals caught by governance

"Self-evolution is a governance subject — not a free parameter."

Governance Metrics

Quantified Governance Effectiveness

Multi-layer metrics measuring decision quality, autonomy maturity, and the gap between stated values and operational reality.

Decision Layer
Task Completion Rate96.8%
Decision Throughput1,240/day
Mean Time to Decision2.3s
Deal Success Rate (Sales)34.2%
Governance Layer
Gate Block Rate8.7%
Human Intervention Rate4.2%
Evidence Completeness99.1%
Policy Violation Attempts0.3%
Evolution Layer
DAG Update Frequency2.1/week
Recursive Iterations847
Rollback Frequency0.4%
MTTR (Incident)18min
All metrics derived fromEnvelope + Gate events

Speed × Stability × Reproducibility — enterprise governance, measured in real-time.

Cross-Universe Envelope Chain

The entire enterprise becomes a governed structure

Universes connect through Envelope chains — evidence, policy, and responsibility flow across boundaries.

Sales Universe
Audit Universe
Compliance
Finance Universe
Envelope Chain
envelope_id: env-2024-1847
parent_envelope_id: env-2024-1846
shared_evidence_refs: [ev-312, ev-313]
policy_snapshot_ref: ps-v4.2.1
origin_universe: sales
chain_depth: 3
Universe Graph
SalesAuditon: decision_executed
AuditComplianceon: audit_completed
ComplianceFinanceon: compliance_verified
Chain KPIs
Cross-Universe Latency<200ms
Chain Failure Rate0.02%
Chain Integrity100%
Departments are not silos.
They are governed nodes.

Scales without breaking — because governance travels with the data.

Verified Skill Marketplace

Extend safely — like GitHub, but governed

Search verified skills...

Signed. Tested. Gate-evaluated. Every skill is a governed artifact.

AUDIT UNIVERSE — BUSINESS IMPACT

Measurable Impact from Day One.

Audit Universe doesn't just automate — it transforms audit quality and coverage.

60%

Reduction in Evidence Collection Time

100%

Trace Reproducibility Rate

3x

Audit Coverage Increase

0

Undocumented AI Decisions

4 weeks

Time to First POC Results

< 1 day

Finding-to-Evidence Linkage

Audit Quality

Every finding is traced to evidence. No orphan conclusions. Gates enforce structural completeness before any output.

Operational Efficiency

Parallel agents evaluate simultaneously. What took weeks of manual sampling now runs in hours with full coverage.

Regulatory Readiness

Pre-mapped to SOC 2, ISO 27001, J-SOX. Audit packages are compliance-ready from the architecture level.

ROI is not about speed. It is about trust that scales.

AUDIT UNIVERSE — POC ROADMAP

From Zero to Audit-Ready in 4 Weeks.

A structured proof of concept that delivers measurable results.

Week 1

Discovery & Setup

Identify 1 audit domain (e.g., expense approval, vendor assessment)

Configure MARIA coordinate system (Galaxy / Universe / Planet / Zone)

Load initial Knowledge Pack (Manual Pack + Criteria Pack)

Deliverable

Configured zone with 3 agents active

Week 2

Agent Pipeline Build

Deploy Evidence Collector + Finding Analyst + Risk Assessor

Configure 4-stage audit gates (Schema / Pre-Alignment / Execution / Post-Audit)

Run first automated evidence collection cycle

Deliverable

Working pipeline with gate traces

Week 3

Integration & Validation

Connect to existing data sources (document store, ERP, ticketing)

Run parallel agent evaluation on real audit scope

Validate reproducibility: same inputs → same findings

Deliverable

End-to-end audit finding with full evidence bundle

Week 4

Report & Decision

Generate audit report with traceable citations

Executive review of findings quality vs traditional process

Compare: time, coverage, consistency, trace completeness

Deliverable

POC report with go/no-go recommendation

No months of integration. No vendor lock-in. Just evidence.

Evidence Package

Every decision comes with a complete evidence bundle.

AI adoption stalls when teams cannot explain decisions to auditors. MARIA OS bundles all supporting evidence automatically with every judgment.

DECISION
Judgment ID
JDG-2024-0892
Result
Approved with conditions
Confidence
87%
EVIDENCE BUNDLE
Complete
Input Snapshot
Frozen inputs at execution time
Evidence & Sources
Referenced data with provenance
Applied Policies
Rules that governed the judgment
Approval Records
Who approved, when, and scope
Execution Trace
Full reproducibility info
Export as audit package for internal/external review

MARIA OS is not about making AI faster.It is about making AI safe enough for society.

Accountability by design. Not by afterthought.

Start Your Audit POC Today.

See MARIA OS in action with your own audit scope. 4 weeks. Full trace. Zero risk.

Schedule Demo

See the full Audit Universe pipeline live with your team

Download POC Brief

Share the business case and technical overview with stakeholders

Talk to an Architect

Design your audit zone together with our engineering team

Judgment does not scale. MARIA OS does.