Wrong Tool
A $500K ML platform for a $5K automation problem. It happens every quarter. Usually after the vendor demo.
AI Profit Quotient™ — Diagnostic
Most companies buy the wrong AI tool because nobody told them which problem they're actually solving. This 8-question diagnostic tells you exactly where your problem sits on the AI spectrum and what to do about it.
From $147 $93 · or $247 with a 30-min strategy call
A $500K ML platform for a $5K automation problem. It happens every quarter. Usually after the vendor demo.
You scoped the entire workflow. The real bottleneck was one step. Six months and twice the budget later, you're back at the same table.
You can't evaluate three proposals if you don't know what you actually need. The vendor who talks most wins. Not the right vendor.
You said “AI” to the board. They heard “experiment.” You didn’t get a budget freeze — you got a 12-month question mark.
8 questions map your business context — industry, function, data state, decision-maker type — to your position on the AI spectrum. Rules-based. BI/Analytics. Predictive ML. Generative AI. You'll know which category fits, and why.
Your Top 10 AI use cases, ranked by what's executable given your data, team, and goals. Plus your Top 3 with a plain-English brief: what it does, what it needs, what success looks like.
One sentence. Personalized to your role, your problem, and your data situation. Not a generic AI pitch. The sentence that stops the budget freeze.
The tool wasn't wrong. The diagnosis was. We fixed the approach, not the model.
This is not from a consulting deck, neither from academic textbooks. This ‘fix’ is designed from doing the work across 10 industries, 4 continents, for clients who needed AI that moved P&L. We observed a pattern of the same misdiagnosis, repeating across different industries. And the ‘fix’ — when applied to European telecom, retail/FMCG, and many more — made the solution click. In its bare bones, it's repositioning the approach before buying the tools.
No model swap. No new data. Just the right diagnosis at the start.
“Without first understanding whether AI is truly needed for your use case and what ROI it can deliver, it's difficult to create real value. The Quickscan gives you exactly that: a clear answer before you commit a dollar.”
★★★★★
“We came in thinking GenAI is all there is. The diagnosis completely changed that — gave us a toolbox and a pathway to find, select, and prioritise with a realistic ROI vision. From zero.”
★★★★★
“I'd been sitting on three vendor proposals for two months. Couldn't tell which one was actually solving our problem versus selling me a platform. The Quickscan cut through it in 48 hours — one use case was real, two were noise. That clarity alone was worth it.”
★★★★★
Free
See where you sit. Decide if the full picture is worth $93.
$93
The complete diagnosis. No fluff.
Recommended for $50K+ decisions
$247
Pressure-test your shortlist before the board.
Most clients choosing a use case above $50K pick the call. The report is your reference map; the call helps you navigate the map.
Guarantee
If this report doesn't save you 10× what you paid in vendor spend, scope waste, or board time, we offer a full refund. No questions.
$93 report. $930 in clarity. That's the floor.
FAQ
Every report is generated from your specific answers. Same questions, different inputs => different output. Two COOs in different industries get different Top 10 lists.
Free Preview if you want to test the methodology before committing. Full Report if you're self-sufficient and ready to act on a ranked use-case list. Report + Call if you're about to make a use-case decision above $50K, or you've already picked a use case and want someone to stress-test it before you take it to the board.
Free Preview: in 5 mins. Full Report: 5–10 minutes after form submission. During beta, up to 24 hours if there's a queue. You'll get an email either way.
We'll regenerate it or refund you. One email. No forms.
Yes. Many clients retake after a failed pilot or a major org change. The spectrum position often shifts. Your Top 3 definitely shifts. Just send an email to get a revised report, or book a call to get it personalized to your needs.
Start with the use case that matches three conditions: your data is clean enough to act on, the problem has a measurable P&L impact, and there’s internal ownership. Most organizations skip condition three — a use case without a named decision-maker never gets built. The APQ diagnostic surfaces all three gaps per use case.
A.R.T. stands for Applicability, Readiness, Transformation. Applicability asks whether the problem actually requires AI — most bottlenecks are process failures, not data gaps. Readiness maps whether the organization has the data quality, team capability, and decision-maker ownership to execute. Transformation defines what “solved” looks like in P&L terms before a tool is ever selected. The diagnostic runs all three gates against your answers and surfaces only the use cases that pass, eliminating the mismatches before any vendor conversation starts.
The AI spectrum runs from rules-based automation (if/then logic, no training data required) through business intelligence and analytics, predictive machine learning, and generative AI at the far end. Most mid-market businesses overestimate where they sit. They try to implement ML or generative AI on problems that a rules-based tool would solve — at a fraction of the cost and timeline. The diagnostic places you accurately before you commit budget.
Three reasons account for 80%+ of failed AI pilots: wrong use case selected (mismatched to business problem), wrong layer of the AI stack chosen (ML model where automation would do), and wrong timeline (expecting 90-day ROI on 18-month infrastructure builds). The APQ diagnostic addresses the first two before any vendor is engaged.
An AI strategy audit maps your existing data estate, current AI initiatives, and organizational readiness against a prioritized set of use cases — then delivers a 30–90 day implementation roadmap. The APQ diagnostic is the entry point: it surfaces the top use cases in 5 minutes. A full audit (typically $10,000+) then validates those use cases against your real data, team, and vendor landscape.