Work With Martin
From AI Strategy to Responsible Deployment
How Martin structures consulting work
Martin works with organizations that have identified a specific AI problem and need an experienced hand to diagnose, build, and govern the solution. Engagements focus on defined outcomes: audits, implementation sprints, systems integration, AI-search visibility, and workshops. Commercial delivery runs through AI Marketing Box. This page explains what Martin takes on, how work is governed, and how to qualify a project.
61-word direct answer
Key takeaways
- Engagements begin with a defined problem, not an open retainer.
- All accounts and vendor relationships are client-owned. Martin never holds custody of client funds or credentials.
- Commercial fulfillment routes to AI Marketing Box; this page documents approach, not pricing.
- Speaking, media, and workshop inquiries follow separate routes from consulting.
Who Martin works with
Martin works with executive teams, marketing and operations leaders, and founders who need AI capability built into their organization. Not studied, not piloted indefinitely, but deployed and operating. The organizations are typically small-to-midsize: lean teams where one person owns several functions, nonprofits with compressed capacity, and professional-services firms where AI can measurably improve delivery without replacing the judgment at the center of the work.
He does not take every engagement. Work is best suited to situations where a specific workflow or problem has been identified, the leadership team can commit to collaboration during the engagement, and the organization is prepared to own and govern what gets built after he leaves.
Problems he is best suited to address
The right fit is a concrete AI problem with a measurable gap: leads that are not being followed up quickly enough, a production process that should be faster, an AI pilot that has stalled at the demo stage, a team that uses AI casually but has no policy, or a website that does not appear in AI-generated answers despite strong organic search performance.
Engagements that do not fit: those that need ongoing managed services without a defined exit, those that require Martin to hold or manage client funds, or general AI curiosity without a scoped problem.
Principle
A consulting engagement should leave the organization more capable, not more dependent. Every deliverable is designed to be operated by the client's team after the engagement ends.
Engagement categories
These are the current engagement types. Each is scoped to a defined outcome and delivered through AI Marketing Box.
Diagnostic
AI Revenue Leak Audit
A diagnostic engagement that maps where AI failures in the revenue workflow are costing the organization: slow lead response, broken handoffs, untracked touchpoints. Produces a prioritized list of fixable gaps.
Implementation
AI Revenue Recovery Sprint
A focused implementation sprint that addresses the highest-priority gaps identified in the audit, connecting lead capture, response, CRM integration, and follow-up into a functioning system.
Integration
AI Systems Integration and Agents
Connecting AI capabilities to the tools and workflows already in use: CRM, project management, communication, analytics. Includes agent design where the workflow calls for it.
AEO / GEO
AI Search Visibility
Structured work to improve how an organization appears in AI-generated search results and answer engines: content architecture, structured data, entity clarity, and citation surface area.
Training
Executive and Team Workshops
Facilitated workshops that move a team from AI awareness to a practical implementation plan, governance policy, or applied skill set. Available as standalone events or as part of a broader engagement.
Partner
White-Label Implementation Support
For agencies, consultancies, and fractional executives who need an experienced AI implementation resource behind their delivery. Structured as a defined support arrangement with clear boundaries.
How work is governed
These safeguards apply to every engagement. They are not optional; they define the structure of working with Martin.
Client-owned accounts
All platforms, tools, and services used in an engagement are set up under client ownership. Martin works as an authorized user, not the account holder.
Direct client payment to vendors
When an engagement requires third-party tools or services, the client pays vendors directly. Martin does not collect and redistribute client funds to vendors.
Role-limited, removable access
Access to client systems and data is scoped to what the engagement requires, documented, and removed at engagement close. The client can revoke access at any time.
Written approvals
Consequential decisions, including tool choices, integrations, content publishing, and agent deployment, require written client approval before proceeding.
Shared project tracking
Work is tracked in a shared space the client can see at any time, with clear task status, decision log, and open questions.
Defined deliverables
Every engagement has a written scope with specific deliverables. Work outside that scope is discussed and agreed before it begins.
No custody of client funds
Martin does not hold, manage, or have fiduciary responsibility for any client funds at any point in an engagement.
Caution
Any arrangement where a consultant holds client funds, controls vendor accounts, or operates without written approvals introduces risk the client cannot see. These safeguards exist to make the engagement auditable and the client the decision-maker throughout.
Is this engagement right for your situation?
The best-fit engagements share a few characteristics. The problem is specific enough to state in one sentence. The decision-maker is available to review and approve work during the engagement, not just at the start and end. The organization is prepared to own the system after delivery, which means someone internal will need to understand how it works.
If the situation is more exploratory, such as general AI education or broad strategy development without a specific implementation target, the workshop formats or a speaking engagement may be a better fit than a consulting project.
Scoping, qualification, and pricing are handled at AI Marketing Box, not on this page.
Speaking, workshops, and media as separate routes
If the goal is to bring AI education to a team, a leadership group, or a conference audience rather than to implement a specific system, the workshop and speaking routes are the appropriate starting points. Those engagements are structured differently from consulting projects and booked through different forms.
For media appearances, podcast interviews, or press inquiries, the contact form with intent set to “media” routes to the right destination.
Frequently asked questions
How do I start an engagement?
The best first step is the contact form with intent set to “consulting.” Describe the problem you are trying to solve and the outcome you are working toward. Scoping, qualification, and pricing happen at AI Marketing Box after the initial inquiry.
Does Martin publish pricing on this site?
No. Pricing is not published here; it is handled through AI Marketing Box where offer structures and pricing are current and reconciled. The contact form routes to that conversation.
Can Martin work with organizations outside Hawaiʻi?
Yes. While Martin is based in Honolulu and works with organizations across the Hawaiian Islands, engagements are conducted remotely for clients outside Hawaiʻi. The forward-deployment approach adapts to distributed work.
What is the difference between a consulting engagement and a workshop?
A consulting engagement ends with a working system: an integration, a configured workflow, a deployed agent, or a diagnosed and remediated problem. A workshop ends with a team that understands something and has a plan. They are complementary, and some engagements include both.
The right entry point depends on how specific the problem is. A defined implementation gap calls for a consulting engagement. A team that needs to develop shared understanding before a project begins calls for a workshop.
Does Martin take on clients in regulated industries?
Some regulated-industry work is appropriate; governance frameworks, team training, and AI-search visibility do not require access to regulated data. Implementation work that involves clinical, financial, student, or legally protected data requires additional scoping and may require qualified regulatory counsel before proceeding.
The qualification conversation at AI Marketing Box is where these questions get addressed.