ClelandCo — The office of Jeremy Cleland
Scoping conversations · By appointment
Two buyer jobs
AI decisions need a named mandate.
ClelandCo offers two AI operating-leadership options: recurring advisory while the client retains authority and implementation, or a scoped fractional executive mandate. A separate visibility practice pairs the live technical-readiness scan with a provider-backed measurement design still in validation.
- AI operating advisory
- Fractional executive mandate
- Visibility method in validation
The free instrument
Paste a public URL to check selected HTML metadata and JSON-LD fields, discovery-file responses, and a limited configured-crawler root policy. The result also names the engine, profile, review, and citation evidence it cannot measure.
A note from Jeremy
A roadmap cannot own its next decision.
AI work crosses product, engineering, security, legal, procurement, and the business line that has to use it. When authority is split across all of them, vendor choices accumulate and pilots can reach handoff without one person able to prioritize, stop, or report on the work.
The fractional seat is for that operating-leadership gap. The mandate names the decisions, systems, reporting line, and implementation boundary. The advisory engagement is narrower by design: it pressure-tests the roadmap while your team keeps ownership. The visibility practice is designed around a separate problem—what answer-engine provider surfaces name and cite—and will scope remediation from observed gaps after its live validation is complete.
The work is designed to be falsifiable. A recommendation carries its criteria. A measurement carries its sample count and uncertainty. An assessment can recommend a smaller engagement, a full-time hire, an internal owner, or no added work yet. If the evidence does not justify the next engagement, the written answer should say so.
Selected Work makes the technical evidence inspectable; About keeps the operator background and its limits in one place. Neither substitutes for a written mandate, client-specific evidence, or reserved decision authority.
The engagements
Three ways to engage.
- AI search visibility measurement and remediation
AI Visibility Measurement
A pre-launch measurement and remediation engagement designed to sample five configured answer-engine surfaces for approved buyer questions. The free technical-readiness scan is live; provider-backed answer sampling is still in validation.Starts with the AI Visibility Baseline · One time, about one week
- AI strategy and advisory consulting
AI Strategic Advisor
An advisory seat for teams already building with AI: a scored use-case roadmap, build-versus-buy recommendations, vendor evaluation, review of work in flight, and criteria the team can run without me.Starts with the AI Adoption Assessment · One time, 1 to 2 weeks
- Fractional chief AI officer and AI leadership
Fractional CAIO
An embedded Chief AI Officer who holds the roadmap mandate, sits in leadership meetings, makes vendor and build-versus-buy recommendations inside agreed authority, and implements named pieces where a handoff would stall the work.Starts with the AI Adoption Assessment · One time, 1 to 2 weeks
Selected work
Inspect the evidence, including its limits.
- Public-page technical-readiness tool
ClelandCo Technical-Readiness Scan
A no-signup check of one public page against a ClelandCo-authored technical-readiness rubric. The result exposes the weights, observed evidence, unmeasured evidence, and ranked gaps rather than presenting the score as an answer-inclusion prediction.Live public tool
- Operating and rehearsal method
AI Contingency Framework
A five-phase method for defining the mission, mapping the operating environment, comparing courses of action, rehearsing failure, and sustaining an AI system after launch. The full method and six rehearsal formats are public.Published framework
The operator
Who you're working with.
I am Jeremy Cleland. I retired from the U.S. Army in 2022 after fourteen years in uniform, eleven in Special Operations as an 18D Special Forces medic. I completed an M.S. in Artificial Intelligence at the University of Michigan-Dearborn in 2025.
ClelandCo applies that operational and technical background to AI decision-making, evaluation, governance, and technical visibility work. The selected-work page carries the public evidence and states the status and limitation of each artifact.
The background explains the working style; it does not replace a written mandate, reproducible evidence, or the limits attached to a recommendation.
Questions
Asked and answered.
- Which of the three engagements fits my problem?
- Choose the AI Visibility Measurement when the question is whether AI answers name and cite the business, you accept the disclosed provider-proxy limits, and you want the evidence gaps remediated after live validation. Choose the AI Strategic Advisor when your team owns delivery but needs recurring senior review of the roadmap, vendors, and evaluation criteria. Choose the Fractional CAIO when the missing piece is an executive mandate: a part-time executive mandate covering prioritization, governance, vendor decisions, reporting, and selected implementation. The first conversation can also conclude that none is justified yet.
- How are scope and fees set?
- After live-provider validation, the AI Visibility Measurement is designed to start with the AI Visibility Baseline; the two leadership alternatives normally start with the shared AI Adoption Assessment. The diagnostic establishes what is actually in scope. Visibility work is shaped by questions, validated provider surfaces, locations, competitors, and the remediation backlog. Advisory work is shaped by use cases, systems, vendors, stakeholders, and risk requirements. The fractional seat adds decision authority, leadership cadence, and implementation load. You receive the scope, term, cadence, boundaries, and fee together before deciding.
- What is a fractional Chief AI Officer?
- A part-time senior executive who holds an agreed mandate for a company's AI function: which use cases move forward, what evaluation and governance gates apply, how vendor and build-versus-buy decisions are made, and what leadership hears. Here the Fractional CAIO is a six-month initial term with a recurring weekly decision cadence; the exact meeting and implementation load is scoped after the AI Adoption Assessment.
- Do you implement, or only advise?
- It depends on the mandate. The strategic advisory engagement is review, working sessions, and written criteria; your team implements. The fractional seat can include implementation on named systems where separating strategy from delivery would stall the work. After its provider path is live-validated, the visibility practice is designed to combine repeated sampling with agreed profile, schema, and citation remediation.
- Can you guarantee ChatGPT will recommend my business?
- No. A consultant or provider cannot control what an answer engine says. The provider-backed measurement path is still in live validation; synthetic fixtures are never reported as measurement. Once validated, the method records its prompt version, surface, model, location, schedule, and sample count. Recommendation classification is heuristic, intervals depend on sampling assumptions, and before-and-after movement is not causal proof.
- Who is behind ClelandCo?
- Jeremy Cleland, a retired U.S. Army 18D Special Forces medic who completed an M.S. in Artificial Intelligence at the University of Michigan-Dearborn in 2025. The About and Selected Work pages separate that background from inspectable technical evidence.
Start here
If the problem is real, let's scope it.
Tell me what is stuck. Netlify Forms processes messages for Jeremy to review; the first conversation can also conclude that no ClelandCo engagement is justified yet.