Two consulting engagements. One operator. Both accountable to the revenue line.
AI companies hyperscaling a product they already built. Operators integrating AI into the stack they already run. Both engagements use the same operator, the same governance discipline, and the same standard — every recommendation lands against a measured business outcome, not a slide.
Pick the room you’re sitting in.
There is no overlap between an AI startup at $5M ARR trying to crack enterprise distribution and a $40M e-commerce operator trying to integrate Claude into customer ops. We do not pretend one engagement covers both. Pick the track. Get the operator who has actually done the work — not the consultant whose deck assumes both rooms are the same.
Built with the people writing the checks
I don't do stock photos.
These are receipts.
Every competitor's landing page has royalty-free logos and AI-written testimonials. These are real payments, real invoices, real work — from the operators Profitalize was forged with.
Signed partnership client. AI Acquisition — an eight-figure operator doing $70M/year in revenue — runs on the same systems baked into Profitalize. Partnership contract on file (Independent Contractor Agreement, The Growth Partner DMCC).
Jon + Profitalize is Dan’s private #1 email & growth expert referral — he sends his top clients to us all the time. Full-stack copy, sequence, and broadcast work across 100M Mafia, Elevator Studio, and The Money Mondays.
Multiple Skool shoutout partnerships, each wired $2,000 via ACH — documented in the envelope above.
Rebuilt Frank's email funnel in 9 days before a launch. The launch did 7 figures in 72 hours. Frank wired 4 more times after that.
Profitalize is Anthony’s lead generation and email traffic broker — we source the leads and run the email traffic behind his affiliate training business.
15+ weeks of direct-deposit retainer work. Rebuilt his email infrastructure + deliverability.
Copy + positioning work for his behavioral-science training programs.
Course launch funnel + email sequences for her documentary-funded education arm.
Expert Kajabi site setup + funnel architecture. Invoice accepted in under 24 hours.
Affiliate + commission dashboard: 165,942 hits, 34,705 sales generated, $332,790.69 in commissions earned, $336,538.13 paid out.
Advisory client. A serial multi-business owner — we profitalized Tax Strategists of America's sales and marketing departments.
Hired for Growth Advisory: a full marketing and sales build for a publicly traded company — lead-to-show speed, the results page rewrite, the homepage rewrite, and the VSL script, delivered as a living execution document.
Hired to run email marketing and drive business growth for Investment Joy — 2.52M YouTube subscribers, 1+ billion views across the channel.
Billed against the business — not the slide deck.
Same standard regardless of track. We set a target against your baseline at kick-off, capture the proof in your workspace, and the ledger either shows movement or we keep working. No retainer drift. No quarterly check-ins where nobody can name what changed.
The shape of every consulting engagement.
Same numbers regardless of track or depth. Captured at kickoff, surfaced in your workspace, audited at close.
What hyper-scaling an AI company actually requires.
Five disciplines that compound. Most AI companies execute one of them well, three of them poorly, and ignore the fifth until enterprise procurement drops the deal. We work all five at once.
GTM architecture
Outbound, PLG, partnerships, channel — sequenced for your stage and your model unit economics. Not generic SaaS GTM; AI-economy GTM where inference cost is part of the math.
Enterprise readiness
SOC 2, data residency, model isolation, evals, red-teaming docs, customer DPA templates. The package that closes the $250k+ contract — not the one that gets stuck in security review for six months.
Retention + expansion engineering
AI products churn differently. Wrong evals → silent dissatisfaction → quiet churn at month 5. We build the outcome-tracking layer that turns "the model is fine" into "this customer just expanded by 4× because we caught the failure mode."
Multi-region launch
EU AI Act, residency, latency-sensitive inference, regional compliance, channel partners per market. The work that turns a US-only AI product into a global one — without legal blowing up the launch.
Board-grade growth metrics
AI ARR is not SaaS ARR. We build the metric framework your board actually trusts — usage cohorts, model-cost-adjusted gross margin, retention-by-use-case, expansion-by-workflow. Stops the "but is this real?" question at the board table.
What AI integration actually requires.
Most "AI adoption" projects fail not because the tech doesn’t work but because no one designed the layer between the model and the business. We design that layer first; everything else follows.
Integration architecture
Where AI plugs into your existing stack — CRM, support, ops, finance, marketing. The pattern that keeps your data sovereign, your costs predictable, and your existing tools working.
Model + vendor selection
Claude vs GPT vs Gemini vs open-source. Hosted vs self-hosted. Vendor lock-in vs portability. We make the call based on your unit economics, your data, and your risk profile — not the loudest sales rep.
Governance + safety
Prompt-injection defense, human-in-the-loop policy, audit trail, rollback, spend caps, hallucination guardrails. The package that lets you ship AI to customer-facing surfaces without the lawsuit headline.
Internal team enablement
Operators are not engineers. We build the patterns, prompts, evals, and feedback loops that let your existing team get value from AI without learning to write code or chase frontier-model releases.
Outcome measurement
Every workflow gets a baseline (how much human time, how much error rate, how much revenue) and a target. AI is good or it gets killed — measured against the actual P&L, not against "tokens saved."
Every phase produces an artifact you can point to.
Not a "monthly check-in" model. Each phase has a hand-off, a signed deliverable, and a measurable checkpoint before the next phase starts.
Discovery
Stakeholder interviews, product/stack audit, workflow map, data-landscape diagram. Grounded in evidence from your specific business — no "industry best practice" pulled from a competitor case study.
Diagnosis
Bottlenecks, opportunities, risks — all scored by impact × effort. Output is a prioritized problem statement, not a list of observations. You can disagree with the priority; you cannot disagree with the evidence.
Design
Track A: GTM topology, enterprise package, retention architecture. Track B: integration design, governance framework, model selection, team enablement plan. You sign off before a single line of config runs.
Deploy
Phased rollout with validation gates between stages. You watch the Proof Ledger fill in real time — you do not wait for a final PDF with screenshots.
Prove
Every recommendation measured against its pre-set baseline. Winners documented and handed off. Losers rolled back with the lesson written into your team’s memory so the next cycle starts smarter.
- Phase 01
Discovery
Stakeholder interviews, product/stack audit, workflow map, data-landscape diagram. Grounded in evidence from your specific business — no "industry best practice" pulled from a competitor case study.
- Phase 02
Diagnosis
Bottlenecks, opportunities, risks — all scored by impact × effort. Output is a prioritized problem statement, not a list of observations. You can disagree with the priority; you cannot disagree with the evidence.
- Phase 03
Design
Track A: GTM topology, enterprise package, retention architecture. Track B: integration design, governance framework, model selection, team enablement plan. You sign off before a single line of config runs.
- Phase 04
Deploy
Phased rollout with validation gates between stages. You watch the Proof Ledger fill in real time — you do not wait for a final PDF with screenshots.
- Phase 05
Prove
Every recommendation measured against its pre-set baseline. Winners documented and handed off. Losers rolled back with the lesson written into your team’s memory so the next cycle starts smarter.
Who this is actually for.
We are selective on consulting — deliberately. Below is the shape of operator we engage with on each track.
AI companies — $1M to $50M ARR, scaling
You have product-market fit and customers paying. Now you need GTM, enterprise distribution, retention engineering, and multi-region scale. The awkward middle between "early traction" and "category leader" — we bridge it.
AI companies — pre-IPO + Series C
You are scaling toward a category-dominance event. Board wants metrics that hold up to diligence. Sales motion needs to look more enterprise than founder-led. We harden it.
Operators — $5M+ adopting AI
Real business, real P&L, real channels. AI is a capability to integrate — not a stack to migrate to. You need an operator who has shipped both sides, not a vendor selling a single tool.
Operators — multi-channel + multi-region
Five channels, three regions, an existing tool stack, a real ops team. AI integration here is mostly governance + architecture work — not a chatbot bolt-on. We design the layer that makes it actually work.
When you should NOT book Consulting.
We tell you this on the intake call. You can save time by reading it here first.
You are pre-product, pre-revenue.
Both tracks need a real business to anchor measurement against. Pre-product AI startups should ship the v1 first. Pre-revenue operators should generate revenue before integrating AI on top of nothing.
You want strategy without execution.
We do not sell standalone strategy decks. If you want "here is what you should do" with no hands on the actual work, a management consultancy is the right fit. We only engage when the output lands as running infrastructure.
You want a vendor recommendation, not an architecture.
If the question is "should I buy ChatGPT Enterprise or Claude Enterprise" we will answer it in 30 minutes for free. The consulting fee is for the architecture, governance, and outcome layer — not the procurement decision.
You are looking for cheaper than Big Four.
We are not. We are different — operator-grade, outcome-bound, smaller scope, faster delivery. If price is the criterion, the Big Four will quote lower. If running infrastructure is the criterion, we are the call.
Same senior operator team across all three.
Difference is how much we own vs. how much you drive. Same Proof-Ledger discipline at every depth.
Fastest ROI
Track A: audit your AI product. Track B: audit your stack + AI integration opportunities. Output: a scored, sequenced list of moves ranked by revenue leverage × effort. Lands as an artifact you can execute Monday.
- Stack + product audit
- Sequenced move list
- Workspace-native deliverable
Audit + execution plan
Audit plus a 90-day execution roadmap. Track A: GTM sequencing, enterprise readiness plan, retention build. Track B: integration topology, model selection, governance design, team enablement plan. You finish with a signed plan.
- Includes the Audit
- 90-day execution plan
- Signed before kickoff
Where most engagements land
We execute alongside your team. Track A: GTM motions live, enterprise package shipped, retention layer running. Track B: AI integrated, governance in place, team trained, outcomes measured. You finish with running infrastructure.
- Includes Audit + Roadmap
- Senior team executes alongside
- Running infrastructure on day 90
Outcome guarantee — no movement = continued work at no charge
Make the consulting accountable to the revenue line.
Whether you are scaling an AI company or integrating AI into the business you already run — the engagement model is the same. Outcome-bound, operator-led, measured from week one.
Apply, or talk to Jon directly first. We tell you within 72 hours which track and depth fits — or which engagement to run instead.