Marketing. Run as a System.
The AI Marketing Operating System for the enterprise
mAI connects strategy, execution, measurement, and optimization through one context-aware intelligence layer, built to work across your existing marketing stack.
Context-Grounded · Governed · Explainable · Human-Led
Built by an operator with 30+ years across product, search, AdTech, and digital marketing. The architecture turns that operating experience into reusable AI marketing IP.
Two ways to deploy mAI
One governed architecture. Choose the operating model that fits your control requirements.
Managed mAI accelerates adoption with an operating partner. Enterprise mAI brings the architecture into your environment for deeper control and integration.
Managed deployment
Managed mAI
Operated with marktgAI. marktgAI operates mAI with your business context, governance, and performance signals for faster time-to-value.
- Full-lifecycle, cross-channel operation
- Faster execution with less manual operating work
- P² measured against documented baselines
Best fit: organizations that want an experienced operating partner without building the system internally.
Private deployment
Enterprise mAI
Deployed within your organization. Deploy mAI within your organization and integrate it with your context, workflows, data, and existing technology environment.
- Built on business context and operating requirements
- Integrated with the existing marketing and data ecosystem
- Governed, explainable, and approval-controlled
Best fit: enterprises prioritizing data sovereignty, integration depth, governance, and internal control.
Integration layer
mAI sits above the stack as an intelligence, orchestration, and governance layer, not a rip-and-replace platform.
Keep the systems your teams already use. mAI adds company context, governed decision intelligence, orchestration, measurement, and learning across them.
Business context, customer and performance data, brand rules, objectives, and operating constraints flow in.
mAI applies context, decision logic, orchestration, governance, measurement, and accountable human oversight.
CRM, analytics, advertising, content, email, social, automation, and reporting remain the systems of execution.
Human accountability spans the entire system, from strategy and brand to budgets, audiences, approvals, privacy, policy, and other material decisions.
Reusable operating IP, not another AI interface.
Architecture, decision logic, governance, measurement, and deployment methods designed to be reused across organizations and integrations.
mAI is reusable AI marketing operating IP: architecture, decision logic, governance, measurement, and deployment methods codified for repeatable use across enterprise environments and integrations.
Framework
A repeatable operating architecture connecting workflows, intelligence, governance, and measurement.
Decision Logic
Documented decision logic that applies organization-specific context to recommendations and actions.
Governance
Human approvals, operating boundaries, evidence discipline, explainability, and accountability.
Deployment Methods
Reusable playbooks for managed, private enterprise, integration, and strategic-partner deployments.
Measured deployment learning feeds back into the operating system and implementation playbooks.
Where mAI fits
Built by an operator. Designed to integrate.
Arnaud Fischer | Founder & CEO | AI Marketing Systems Architect
mAI turns 30+ years across product, search, AdTech, digital marketing, and growth into a reusable operating architecture. The mAI Framework codifies that experience into decision logic, governance, deployment, and measurement.
Digital products and search operations.
Marketing, advertising, data, and digital ecosystems.
Operating knowledge encoded into the mAI Framework.
Track Record
Proof with the context attached
How to read the evidence
Evaluate mAI through documented evidence context, operating targets, and validation standards, not unsupported performance promises.
Reported outcomes tied to a specific engagement and evidence context.
Objectives defined against documented baselines before optimization.
Claims supported by an explicit validation standard and evidence trail.
Aggregate range · applied evidence
Financial Services · client acquisitions
Manufacturing · qualified leads
B2B Technology · SQLs
Sustainable Manufacturing · qualified leads
SaaS · trial-to-paid conversion
Healthcare · patient engagement
DTC eCommerce · checkout completion
Consumer Brand · social engagement
Reported outcomes for the specific engagement described. Not a forecast or guarantee — see the individual case for context and evidence.
Operator credibility
Built from real platform and marketing operations
Experience across enterprise software, search, AdTech, digital platforms, and growth informs the operating architecture behind mAI.
