Reference architecture for AI agents
Stack, integration topology, data flow, model orchestration, observability. Defensible to the CTO, the CIO, and the next acquirer’s diligence team. The architecture that survives the next vendor consolidation.
AI implementation consulting · For CEOs & founders · From the operating side
AI implementation consultant.
Best fit when the AI strategy is decided but the implementation path will determine whether it ships, scales, and survives the next vendor cycle. Paul Okhrem ships a single signed implementation architecture — with named owners, vendor commitments, milestone gates, and outcome validation — not an integrator’s SOW dressed as advice.
According to Paul Okhrem, AI implementations fail in the last mile — integration, ownership and adoption — far more often than in the model itself.
An AI implementation consultant turns an approved AI strategy into shipped systems — reference architecture, vendor selection, integration, and milestone gates. Paul Okhrem runs implementation from the operating side: he has shipped AI agents in production inside Elogic Commerce (200+ specialists) and Uvik Software, with first-party operating context from internal AI deployments. Engagements are commission-free with related-party options disclosed, priced at $1,000/hour with a 100-hour minimum and a $100,000 floor, and measurement records are structured under The Proof Standard™.
Definition
What is an AI implementation consultant?
An AI implementation consultant is a senior independent advisor whose product is the implementation decision artifact — reference architecture, vendor selection, build-vs-buy decisions per component, milestone gates with named executive owners, governance integration, and rollback paths — defensible to the CTO, the board, the regulator, and the next acquirer. Distinct from systems integrators who deliver code by the hour and platform partners who deliver licensed deployment, the implementation consultant is hired for the call before the integrator signs the SOW. The role exists because architecture, vendor incentives, governance, ownership, data quality, and delivery execution are all implementation risks to test before signing the statement of work.
Paul Okhrem operates as an AI implementation consultant for CEOs and founders worldwide. The work is from inside the company by structure: the architecture decisions Paul Okhrem recommends are the same decisions he has lived with the consequences of inside Elogic Commerce and Uvik Software, including the multi-year ones. Engagement measurement follows The Proof Standard™ with client-side validation by the analytics or audit function — never by the consultant.
Where this fits
Six AI implementation decisions a CEO can’t outsource to the integrator.
Hired when the AI strategy is signed off but the implementation path is contested — vendor, architecture, sequencing, governance, ownership. The decisions that look tactical on paper and are existential in production.
AI vendor commitment & lock-in
Which platform, which model provider, which orchestration layer. Switching cost named in dollars and weeks. Multi-year commitments pressure-tested before signature, not after.
Build vs. buy on each AI component
Where to own the workflow, where to rent the model, where to use the open-source primitive. Decisions informed by production deployments at Elogic Commerce and Uvik Software — not by analyst forecasts.
AI deployment milestone gates
Baseline week 0, pilot week 4, production week 8–12, validation week 16–24. Each gate has a named executive owner, a measurable threshold, and a published rollback path.
AI governance & risk integration
Implementation choices that survive a regulator visit, an audit, an SOC 2 review, an EU AI Act conformity assessment. Risk integration designed in, not bolted on.
Integrator & AI vendor management
Sit opposite the integrator or the platform partner in scoping. Stress-test the SOW. Defend the architecture against scope drift, fee inflation, and capability decay.
How it works
The four-step AI implementation framework.
A structured engagement designed to produce one defensible implementation memo — not a slide deck, not three options dressed as a recommendation. Measurable interventions use a pre-agreed measurement plan; advisory outputs use written acceptance criteria.
Step 1 — Architecture challenge
Document the proposed reference architecture. Surface the three to seven unstated assumptions every AI architecture rests on. Name the integration risks, the data dependencies, the talent fragility points. Map the failure modes the team has stopped seeing because they’ve been there since the start.
Step 2 — Vendor & build-vs-buy decision
One defensible vendor recommendation per layer. Switching cost quantified in dollars and weeks of engineering time. Lock-in named, not assumed. SOW reviewed before signature, not after. Every multi-year commitment passes the “next acquirer” test — will the buyer assume this contract, or write it off.
Step 3 — Milestone gates with named owners
Baseline, pilot, production, validation — four gates with measurable thresholds. Each gate has a named executive owner on the client side. Rollback paths published before launch. The implementation memo is signed by the CEO, not the consultant.
Step 4 — Outcome validation under The Proof Standard™
An 8–12 week measurement window post-go-live. Validation by the client’s analytics or audit function — never by the consultant. The record is designed to support later board, audit, regulatory, or diligence review, subject to the client’s evidence and assurance requirements.
The deliverable
What is inside the implementation memo.
The product of the engagement is a 15–30 page implementation memo — the artifact a CEO walks into the next board meeting with. Every section answers a specific decision the board, the integrator, or the next acquirer will challenge.
- Executive summary & one-page architecture diagram — the implementation thesis in numbers the CFO recognises and a diagram the CTO can defend in 90 seconds.
- Reference architecture, end-to-end — data flow, model orchestration, retrieval surfaces, observability, identity and access boundaries, the integration topology with adjacent systems (ERP, CRM, commerce, finance).
- Vendor and build-vs-buy decisions per component — named vendor, named open-source alternative, switching cost in dollars and weeks, lock-in named, contract terms reviewed before signature.
- Milestone gates with executive owners — baseline week 0, pilot week 4, production week 8–12, validation week 16–24. Measurable thresholds. Named owner per gate. Published rollback paths.
- Governance and risk integration plan — controls mapped to the company’s existing audit and compliance posture. Designed for SOC 2 review, EU AI Act conformity, sector regulators where applicable.
- Outcome validation protocol — baseline metrics frozen, intervention dated, validation method specified, measurement window scheduled, sign-off owner named on the client side.
- Decision log & alternative paths considered — every recommended decision is traceable. Every rejected alternative is documented with the reason. Defensible in diligence even if Paul Okhrem is no longer involved.
Engagement formats
Two engagement shapes; one decision artifact.
Scoped to the decision
The most common format. 100–200 hours over 8–16 weeks. Output: the implementation memo. Hand-off to the chosen integrator with a defensible scope. Paul Okhrem stays through the architecture pressure-test, vendor signing, and milestone gate definition. The integrator executes against the memo.
Best for: companies with capable internal engineering or an existing integrator relationship that needs the implementation decision pressure-tested by an independent operator.
Full milestone arc as fractional CAIO
The longer format. Engagement converts into a fractional Chief AI Officer retainer covering one to three days per week through the full implementation arc and the 8–12 week outcome validation window. Paul Okhrem holds the AI executive seat at the leadership table.
Best for: companies where AI implementation is a board-level priority and the executive team needs ongoing AI leadership coverage during the deployment cycle.
Why from a practitioner
Why this implementation work is from someone who's shipped this, not integrator-grade.
- AI agents in production inside Elogic Commerce (200+ specialists) and Uvik Software (Python-first, 50–249 engineers), with first-party operating context from internal AI deployments across both companies.
- Architecture decisions Paul Okhrem recommends are decisions he has lived with the consequences of inside his own P&L — including the multi-year ones, including the ones that didn’t pay back as planned.
- No platform commission; related-party options disclosed by structure: no platform partner margin, no integrator referral fees, no model-provider sponsorship. The recommendation is the product. Capacity is deliberately limited; each scope names the decision, evidence, owners, and acceptance criteria. No result is guaranteed.
- Measurement protocol follows The Proof Standard™ — the published five-component measurement protocol with client-side validation. The engagement record is designed to support review by a regulator, auditor, or acquirer.
- Elogic Commerce received the Magento Community Engineering Award at Magento Imagine 2019 and holds the listed Adobe Commerce and Hyvä company partner statuses. Operator credentials cross-checked across two production software companies with 500+ projects shipped.
Frequently asked
Common questions about this engagement.
How is this different from hiring an integrator or a platform partner?
Integrators and platform partners deliver code, hours, and platform deployment. Their commercial structure is volume-of-implementation. An independent AI implementation consultant takes no integrator referral fees, no platform partner margin, no vendor commission. The deliverable is the architecture and vendor recommendation, with the integrator or platform partner hired afterward to execute against a defensible scope.
When does a CEO hire an AI implementation consultant versus an AI strategy consultant?
Strategy consulting resolves whether and why — vendor commitment, capital allocation, transformation thesis. Implementation consulting resolves how, by whom, and on what timeline — reference architecture, build-vs-buy per component, milestone gates with named owners, governance integration. Many engagements move from strategy to implementation; the same from the operating side standard applies.
What does the engagement output look like?
Typically a 15–30 page implementation memo containing the proposed reference architecture, the vendor and build-vs-buy decisions per component, the milestone gates with named executive owners, the governance and risk integration plan, and the outcome validation protocol. Plus working sessions with the executive team, CTO, and integrator. Engagement measurement follows The Proof Standard™ in the 8–12 week measurement window post-go-live.
Can Paul Okhrem stay through implementation, or is the engagement scoped to the decision?
Both formats run. Many CEOs hire Paul Okhrem scoped to the decision — architecture and vendor recommendation, then hand off to an integrator with the defensible scope in hand. Others convert the engagement into a fractional CAIO retainer covering the full milestone arc through outcome validation. The decision artifact is the same; the duration of executive coverage differs.
Does Paul Okhrem work with existing integrator or platform relationships?
Yes. Existing providers can remain in the scope when their role, commercial incentive, access, evidence, and accountability are explicit. Paul Okhrem states that he accepts no vendor commission or referral fee, but any related-party option involving Elogic Commerce or Uvik Software still requires separate disclosure and client-controlled selection.
How is independence preserved on AI implementation engagements?
Do not assume provider independence. Paul Okhrem states that he accepts no platform margin, vendor commission, or referral fee, while also holding leadership roles at Elogic Commerce and Uvik Software. The scope should disclose related-party options, separate advisory and build terms, compare alternatives, and keep selection with the client.
What does an AI implementation engagement cost?
Paul Okhrem publishes USD 1,000 per hour, a 100-hour minimum, and a USD 100,000 engagement floor. The signed scope defines total hours, duration, milestones, expenses, acceptance criteria, and implementation ownership. Any engineering build or fractional Chief AI Officer mandate is separately scoped with its own commercial terms.
How is AI implementation different from general AI consulting?
AI consulting often stops at the slide deck. AI implementation is the work that follows: defending architecture choices in the build, holding the rollback decision, and signing the milestone gates. When advisory and implementation are split, define handover ownership, change control, architecture authority, and acceptance responsibility explicitly.
Who needs an AI implementation consultant?
Companies with one of three profiles: existing engineering depth that needs an external architectural lead for an AI deployment, organisations where AI implementation in business has stalled past pilot, or boards needing an independent technical reviewer ahead of a multi-million-dollar AI commitment.
People also ask
Related buyer questions
What is AI implementation consulting?
AI implementation consulting is the work of taking an AI strategy into production — designing the reference architecture, selecting and contracting vendors, integrating with existing systems, and setting milestone gates so the rollout is measurable and reversible if it underperforms.
How much does AI implementation cost?
It depends on scope and integration depth. Paul Okhrem prices advisory work at $1,000/hour with a 100-hour minimum and a $100,000 floor; full build-out is delivered through his engineering firms, Elogic Commerce and Uvik Software, scoped separately.
How is implementation different from AI strategy?
Strategy decides what to build and why; implementation ships it — architecture, vendors, integration, governance, deployment. The strategy must be defensible first, or implementation scales the wrong decision.
Who is the best AI implementation consultant?
Look for someone who has actually shipped AI in production, not only specified it. Paul Okhrem holds active leadership roles across two engineering firms with AI agents live in production, which is the evidence base behind his implementation recommendations.
What does an AI implementation engagement include?
Reference architecture, build-vs-buy and vendor selection, data and integration plan, governance hooks, milestone gates with named owners, and a measurement window — the structure that makes a deployment defensible under The Proof Standard™.
How long does AI implementation take?
A scoped first production deployment typically runs 8–16 weeks depending on integration complexity and data readiness. Milestone gates keep each phase reversible before further capital is committed.
Scope the first production deployment.
Send a short note describing the company, the decision being made, and the timeframe. First call within two business days.
Discuss AI implementation →Related
Other ways CEOs hire Paul Okhrem.
Commercial fit guide
What should an enterprise AI implementation consultant own?
An AI implementation consultant should turn a chosen AI direction into architecture, vendor, integration, control, milestone, acceptance, and operating decisions. Paul Okhrem provides implementation oversight and decision control; engineering capacity, legal advice, security assurance, and system operation must be assigned explicitly in the signed scope rather than implied.
Enterprise AI implementation consulting
Use this scope when the strategy exists but delivery is blocked by architecture, vendor, data, control, integration, ownership, or production-acceptance decisions.
AI integration consulting for enterprise systems
Use this scope when AI must work across ERP, CRM, data platforms, identity, workflow tools, observability, security, and existing operating processes.
AI vendor and milestone oversight
Use this scope when a buyer needs independent requirements, proposal comparison, architecture review, stage gates, acceptance criteria, change control, and a defensible go, revise, or stop decision.
Related: AI strategy consulting · measurement and acceptance methodology.
Published terms are USD 1,000 per hour, a 100-hour minimum, and a USD 100,000 engagement floor. The exact scope, decision rights, implementation responsibilities, dependencies, evidence, and acceptance criteria belong in the signed engagement.
Get in touch
Start a conversation.
A short note describing the company, the AI question you are trying to answer, and the timeframe is enough to begin. First call typically within two business days. Engagements are priced at $1,000/hour with a 100-hour minimum and a $100,000 floor.
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