Governance
Establishes authority, constraints, provenance, and the rules that must not be bypassed.
Declarative runtime-governance module
Turn governed authority into bounded runtime state.
BGC — Behavior–Governance–Control — resolves approved behavior, governance, and control inputs into usable runtime state. It gives automation, AI-assisted operations, support systems, and platform controls a common way to determine what may happen, why, and under whose authority.
IBERION PORTFOLIOBGC — Behavior–Governance–ControlGoverned inputs · derived runtime state
Turn standards into operating behavior
Bound AI, automation, and cost decisions
Create evidence for service and architecture governance
The system in context
Observe, decide, enforce, learn.
Declarative operating model
Four responsibilities. One traceable projection.
BGC is more than a configuration format. Runtime behavior is derived from governed inputs with explicit precedence, provenance, and validation.
Control
Exposes, limits, or disables capability within the authority that governance has established.
Behavior
Defines the operating choices a governed component may select inside those limits.
Runtime state
Projects the validated result for consumers; it is derived state, not an alternate source of authority.
AI may advise, classify, or recommend inside an approved workflow. It does not automatically become governance authority, and not every internal BGC consumption path is represented as fully wired.
The connective operating layer
BGC is useful almost everywhere behavior needs a boundary.
Each surrounding system keeps its own responsibility. BGC supplies a reusable way to evaluate rules, constrain action, record decisions, and expose evidence across those boundaries.
Behavior–Governance–ControlBGCRules → decisions → bounded action → evidence
Defined integration gatePersona AI + Diago PlataNative BGC conceptSAIS Established architectureIGMNative BGC capabilityWatchers, workers & automation
Approved response boundaries, role ownership, fact provenance, escalation, cost and latency evidence, and ITIL-linked service records.
The live support path is deterministic; unrestricted generative dialogue is not claimed.Standards as Implemented Service—pronounced “says”—turns written standards and policies into governed service behavior.
The flagship commercial and architectural expression of BGC.IGM provides governance and learning structure; BGC is its runtime execution arm for applied behavior controls and decision evidence.
IGM and BGC remain distinct—not synonyms.Parallel capabilityCost controlIGM includes cost-governance views; BGC provides the reusable runtime-boundary pattern that can constrain approved automation and model activity.
The direct IGM-cost-to-BGC enforcement linkage still requires confirmation.Defined integration gateITIL service operationsIncident, problem, change, request, ownership, evidence, recovery, and escalation can pass through explicit BGC behavior gates.
ITIL-aligned; no ITIL certification or tool accreditation is claimed.Database-backed rules, bounded enforcement, runtime projections, control flags, and decision history support repeatable operational control.
Current watcher state must be verified before any active-enforcement claim.BGC’s flagship concept
SAIS: the standard does not stop at the document.
SAIS—Standards as Implemented Service—describes the move from policy that people must remember to service behavior that systems can evaluate, apply, and evidence.
Standards & policy→BGC rule boundary→Service behavior→Decision evidence
BGC’s rule model carries framework and control references for standards packs including NIST, ITIL, ISO 27001, and SOC 2. TOGAF phase tagging and compliance views exist in the adjacent IGM namespace.
What it delivers
Capability, made specific.
Behavior-rule evaluation
Watcher and control-plane governance
Bounded enforcement
Policy and evidence separation
Runtime event generation
Fail-closed authority limits
Deployment and commercial shape
One module, many bounded jobs.
Persona-AI and support-governance boundary
SAIS standards implementation layer
Cost-aware automation and model controls
IGM execution, watcher, worker, and control-plane governance
Current evidence boundary
What can be said now.
Confirmed as a full module with code and schema documentation. Existing watcher and metadata defects must remain visible rather than being hidden by a general maturity claim.
Portfolio publications
Written about the system, in public.
These are the existing Iberion and Meridian articles most directly related to this capability. They establish the portfolio’s published problem framing and architectural thesis; they are first-party publications, not independent certification.
Iberion / Meridian public writingWeek 9: Why AI Needs Governance LayersRuntime AI governanceRead article ↗Iberion / Meridian public writingWeek 10: From Automation to Autonomous InfrastructureAutonomous operating infrastructureRead article ↗Iberion / Meridian public writingWeek 12: The System Nervous System — When Platforms Learn to SteerSensing, coordination, and operational feedbackRead article ↗Iberion / Meridian public writingWeek 16: Platform IntelligencePlatform-intelligence maturityRead article ↗
Standards and external context
Independent sources behind the operating model.
These official sources establish the surrounding disciplines. They do not certify BGC or independently verify Iberion implementation, performance, or qualification.
NISTNIST AI Risk Management FrameworkOrganizes trustworthy-AI risk activity around Govern, Map, Measure, and Manage across the AI lifecycle.Read official framework ↗NISTNIST SP 800-53 Rev. 5Provides a catalog of security and privacy controls that can inform governed control families and implementation profiles.Read official publication ↗PeopleCert · ITILITIL Management PracticesProvides service-management practices for support, incident, problem, change, monitoring, requests, and continual improvement.Explore official practices ↗The Open GroupTOGAF StandardProvides a configurable enterprise-architecture method and framework for aligning architecture work with organizational outcomes.Read official overview ↗Open Policy AgentPolicy decisions and enforcementExternal implementation context for separating policy decisions, enforcement points, and decision logging.Read documentation ↗OpenTelemetryObservable runtime signalsExternal context for using complementary traces, metrics, and logs to understand system behavior.Read documentation ↗
Continue exploring