Maturity Model
Semantic Drift Intelligence™ Maturity Model
Most organizations are ready to govern meaning. Few have a safe path to get there.
This four-phase model defines the only reliable path from semantic visibility to safe, closed-loop remediation.
- Understand the risks your current state creates
- See why each phase must be earned before the next
- Map a safe path toward prevention and remediation agents
Why a maturity model for semantic drift
Semantic governance isn’t a tooling problem — it’s an organizational readiness problem. Semantic Drift Intelligence (SDI) provides the operating model for meaning, governing how business terms evolve, how definitions are enforced, and how trust is maintained across your data supply chain.
Capability progression
From visibility to closed-loop operations. Each phase builds the capabilities needed to institutionalize semantic integrity.
Risk posture
From unknown drift to governed remediation. Understand your exposure to semantic drift and how it shrinks at each phase.
Value unlock
From insight to automated, auditable action. Each phase unlocks new efficiencies and strategic capabilities.
The Four-Phase Maturity Model
A proven progression to institutionalize semantic integrity across your organization.
1
Establish the control plane
Capability: Semantic observability and trusted scoring.
Organizations move from fragmented meaning to semantic observability. Drift becomes measurable, explainable, and prioritized. The Semantic Registry is populated, drift detection is running, and teams actively use the Drift Viewer.
The psychological shift: This is the moment when teams finally understand what’s changing and why — and until that trust exists, governance is performative and agents are dangerous.
- Risk posture: From unknown drift to measured and explainable drift.
- Value unlock: Reliable visibility into semantic stability.
- SDI focus: Implementation, Semantic Registry, drift detection, Drift Viewer.
2
Activate governance
Capability: Repeatable, accountable semantic governance.
Organizations move from visibility to governed response. Ownership is assigned, workflows are defined, and audit logging becomes the center of gravity. Semantic change becomes a managed operational workflow.
The psychological shift: The shift here is from ‘we see drift’ to ‘we own drift’ — and ownership is what makes agents safe to introduce later.
- Risk posture: From ad hoc response to governed response.
- Value unlock: Semantic drift becomes a managed workflow.
- SDI focus: Governance workflows, ownership, audit logging.
- Add-ons: Semantic Model Hardening, BI Governance Accelerator.
3
Drift prevention agents
Capability: Predictive stability and contract enforcement.
Organizations move from reactive governance to predictive stability. Prevention agents operate against a hardened semantic contract, flagging potential drift before it impacts critical metrics or reports.
The psychological shift: Prevention agents only succeed when humans already agree on the semantic contract — otherwise the agent becomes another source of noise.
- Risk posture: From responding to preventing.
- Value unlock: AI enforces the semantic contract safely.
- Preconditions: Trusted scoring, ownership, workflows, hardened definitions.
4
Active remediation agents
Capability: Closed-loop semantic operations.
Organizations move from prevention to closed-loop remediation. Agents propose and, where approved, execute safe changes, document lineage, and route exceptions to humans.
The psychological shift: This phase works only because the organization has already demonstrated discipline — without that foundation, automated remediation becomes a liability, not an asset.
- Risk posture: From human bottlenecks to AI-assisted remediation.
- Value unlock: Continuous, automated, auditable remediation.
- Preconditions: Proven agent judgment in prevention scenarios.
Offering Mapping
Each phase aligns directly with the Professional and Enterprise tiers — and the add-ons — already defined on our pricing page. The model below uses the same terminology to ensure consistency.
Phase 1
Establish the control plane
SDI Professional + core implementation: Semantic observability, Registry, and drift detection.
Phase 2
Activate governance
SDI Enterprise + Hardening + BI Governance Accelerator: Governance workflows, ownership, audit logging.
Phase 3
Drift prevention agents
Prevention agents (available only after Phase 2): Predictive stability and contract enforcement with AI.
Phase 4
Active remediation agents
Remediation agents (available only after Phase 3): Closed-loop semantic operations with self-healing.
Where is your organization today?
- Do we lack visibility into semantic drift?
Risk: Meaning changes silently, and no one knows why metrics shift. - Do we see drift but have no ownership model?
Risk: Incidents resolve randomly — or not at all. - Do we have governance but no AI support?
Risk: Humans become the bottleneck for semantic stability. - Are we exploring agents without foundational readiness?
Risk: Automation amplifies drift instead of preventing it.
Why sequencing matters
Skipping phases doesn’t just increase risk — it breaks the entire operating model. Each phase creates the conditions that make the next one safe, predictable, and effective. This is true for every enterprise, regardless of industry.
- 1️⃣ Phase 1 builds trust
- 2️⃣ Phase 2 builds ownership and accountability
- 3️⃣ Phase 3 builds confidence in agent judgment
- 4️⃣ Phase 4 delivers safe, closed-loop automation
Ready to assess your semantic drift maturity?
Take the first step toward a trusted, self-healing semantic layer. Schedule a strategy session with our team.