Questions about the mAI Framework, deployment, evidence and governance

The mAI Framework is marktgAI’s marketing intelligence architecture connecting enterprise context, the AI Marketing Brain, AI Marketing OS, Human Command, integrations and evidence-based measurement.

It is the operating layer that connects Plan → Execute → Measure → Optimize across approved marketing workflows and systems.

It is the decision-support layer that applies approved organizational context and performance signals to analysis, hypotheses, recommendations, prioritization and learning.

Human Command defines the decisions, permissions, review points and approvals that remain accountable to people, especially strategy, brand-critical creative, material budget or audience changes, policy-sensitive actions and regulated content.

Managed mAI is the operating model where marktgAI helps run defined parts of the marketing lifecycle using the mAI Framework while material decisions remain subject to Human Command.

Custom Enterprise mAI is for organizations requiring deeper company-specific context, integrations, deployment control, data-sovereignty considerations or governance requirements.

Not by default. mAI is designed to work as an intelligence, orchestration and governance layer around approved analytics, CRM, advertising, content, email, social, commerce and automation systems where integration is appropriate.

No. Productivity and Precision are measured against documented baselines and relevant KPIs. Case-study outcomes are modeled from illustrative scenarios. They are not client results, universal forecasts or guarantees.

No framework-level claim can establish deployment compliance. Applicable legal, privacy, security, residency, vendor, consent and regulatory requirements must be validated for the actual use case, jurisdiction and architecture.

Named-company mAI Hub pages are illustrative public-context models unless explicitly stated otherwise. Case studies are modeled scenarios with modeled outcomes, not client results. The Evidence Methodology explains the distinction.

marktgAI separates demonstrations, observations, operating targets, modeled scenario outcomes and validated claims. Measurement definitions, baselines and attribution limits are made explicit before conclusions are generalized.

Start with your operating context, current stack, governance requirements and measurable objectives.