I help operators leverage the three layers that actually run a company. So growth scales the business instead of breaking it. Risk management, KPI architecture, AI transformation - same discipline, three lenses.
M.Sc in AI · Remote, regulated industries
5 quick questions. Get a personalized growth stage diagnosis based on Greiner's Growth Model - used by Fortune 500 companies to navigate scaling challenges.
Three things I do well - and most consultants don't.
I find the leaks, bottlenecks, and risks before they show up in the numbers. While there's still time to fix them cheaply.
Risk management is my muscle. Prioritize what matters. Contain what's brittle. Prepare for what's coming - so problems get smaller, not larger.
Flexible, agile systems that bend without breaking. Designed so your company can grow fast, stay fast, and use minimum resources.
Across people, processes, and technology. AI when the diagnostic shows it earns its way in - not as the default.
Every gap between your people, systems, and processes that you don't catch at the current scale costs roughly 10x more to fix at the next one. Operator-led diagnostic catches it cheap. Read the full 10x Rule article ->
Where time, money, and attention drain quietly. Process inefficiencies. Tool fragmentation. Decision delays. Handoff failures.
Where work piles up and waits. Founder dependencies. Single approval points. Manual reconciliation. Knowledge silos.
Where systems are fragile but no one's measuring. Architectural debt. AI compliance gaps. Regulatory exposure. Talent concentration.
The leverage doesn't sit in one place. It hides across people, systems, and processes - usually in the overlap. I look at all three. Best practices are a starting point, not the answer - what we build fits your culture, budget, and goals.
Culture, leadership, decision rhythm, founder dependencies, team dynamics. The layer where the next phase of growth usually breaks first.
See use casesWorkflows, handoffs, governance, approval cascades, operational leaks. The day-to-day cost of running a company in a way it's outgrown.
See use casesTech debt, system fragility, scaling constraints, data foundation, AI readiness. AI shows up here - when the diagnostic earns it.
See use casesMost operators don't search for "Scale Readiness Assessment." They search for what's keeping them up. Here's the work, framed the same way.
Scale Readiness Assessment. Operator-led diagnostic across people, systems, and processes. Specific list of what's about to break, ranked by severity and estimated cost-if-ignored. Plus a written 90-day action plan.
A 90-day plan your team can execute internally. Recovered leadership time. Confidence the next quarter doesn't ambush you.
Every gap caught late costs roughly 10x more than the same gap caught early.
Three-Pillar KPI Audit. Outcome / Execution / Foundation. Surface Goodhart traps and Conway's-Law violations. Hand back a smaller, coupled, honest measurement stack with a metric registry template.
30-50% of leadership time recovered from "is this number even real?" Earlier signal on what's actually working.
Wells-Fargo-class failures don't announce themselves. The dashboard works exactly until it doesn't.
AI Adoption Diagnostic. Map where AI actually earns its way in across people, systems, and processes. Identify the 2-3 highest-leverage workflows. Reject the bad fits.
Stop paying for tools nobody uses. Real productivity gains in the workflows where AI fits. Clarity on what NOT to automate.
The compounding AI tax. Configuration burden grows. Junior talent doesn't develop judgment because the AI did the work first.
Growth-Readiness diagnostic. Same People + Systems + Processes lens, specifically targeted at where the company is going, not where it is.
Know which leaks will get expensive at 2x size before you hit 2x. Hire into a working org, not a broken one.
Scaling broken systems means breaking them faster.
Fractional / Interim Executive. 3-12 month embedded engagement. Remote, hands-on, operator-led. Head of Product, Fractional COO, Interim PMO, AI Lead.
Senior leadership in the seat now, without the full-time commitment. The work documented so the eventual hire inherits a working machine.
Every month without that seat filled is compounding friction the org will pay for later.
Investment Due Diligence. Same diagnostic muscle, applied to target companies pre-investment - or to existing portcos during quarterly reviews. Operational, technical, AI readiness.
Catch the operational risk the financial DD missed. Catch the team risk the founder interviews missed. Before you commit capital.
Post-investment, you find these things at board meetings.
Custom AI Workshop + Knowledge Transfer. Built around the team's actual workflows, not generic AI 101. Each participant leaves with 2-3 prompts or agents they use in their job next week.
AI literacy at the team level. The 2-3 workflows you wanted automated, owned by the people who do the work.
The configuration tax grows. People configure tools instead of using them.
Same offer, same flat rate, delivered async-friendly across EU, US, UK, and beyond. Time zones, contracting, and payment all pre-engineered for cross-border work. See how remote engagements work →
Most operators considering external help look at one of four other models. Here's how they actually compare - and where one of them is genuinely the better call.
| This workMay Mor / Scale with May | Big 4 / Strategy firmMcKinsey, BCG, Bain, Deloitte tier | Boutique consultancy10-50 person specialty firm | Fractional marketplaceBolster, Continuum, Toptal Exec | Hire in-houseFull-time COO / Head of Ops | |
|---|---|---|---|---|---|
| Time to start | 1 week (free 30-min intro, then kickoff) | 4-12 weeks (RFP, pitch, contracting) | 2-4 weeks (sales call + proposal) | 2-4 weeks (browse + interview candidates) | 8-16 weeks (search + offer + notice) |
| Time to first written read | 6 weeks end-to-end | 3-6 months (Discovery phase only) | 6-10 weeks | 1-2 months post-ramp | 3-6 months post-hire ramp |
| Total cost (first engagement) | €4,000 flat | $100K - $1M+ | $30K - $150K | $8K-15K/mo × 3-12 months | $200K-400K loaded annual + ramp |
| Delivery model | Remote-first, async-friendly | On-site team residency | Mixed remote / on-site | Mostly remote | Wherever your team works |
| Who delivers the work | One operator (10+ yrs fintech, M.Sc AI) + AI tooling | 5-15 person team: partner + manager + associates (mostly MBAs, rarely shipped product) | 2-5 person team, mix of ex-operators and career consultants | One vetted operator (the fractional exec) | One full-time hire |
| Implementation philosophy | DIY-first. Recommendations list the cheapest and most in-house option first. I only sell implementation when the diagnostic shows you can't. | Discovery designed to surface follow-on work. Pilots, roll-outs, embedded delivery - billable hours scale. | Project-scoped. Some stay for implementation, some hand off. | Embedded - they do the work, knowledge transfer is incidental. | Owns the work permanently. Knowledge stays in the org. |
| Scope flexibility | Custom. Same diagnosis can produce different fixes for different companies. | Playbook-driven; consistent framework across clients | Tied to the firm's specialty (pricing, M&A integration, etc.) | Tied to the operator's prior career | Tied to one person's experience |
| Commitment shape | One short engagement. Money-back guarantee. No retainer. | Multi-phase, often multi-year | Fixed project, sometimes followed by retainer | 3-12 month minimum | Permanent (with severance risk) |
| Best fit when | Series A-C, regulated or scaling, you want a senior read fast and want to execute most of it yourselves | $500M+ org, board-level visibility, multi-year transformation budget, the brand on the deck matters | You need deep domain expertise (pricing, M&A integration, regulatory) that justifies the spend | You need someone in a seat for 6-12 months, not a one-time read | You're sure the role is permanent and the right person is available |
Listed prices apply to Israeli companies and fully remote engagements anywhere in the world. On-site work outside Israel adds travel and per-diem fees, quoted per trip.
This isn't a knock on the other models. They're built for different jobs. Here's when one of them is actually the better choice:
You're a Fortune 500 board reviewing a $50M+ transformation, you need McKinsey on the cover slide for political cover, and your timeline is measured in fiscal years. Their machinery is built for that. Mine isn't.
You have a specific problem that lives in one discipline: pricing strategy, M&A integration, FDA regulatory, supply-chain optimization. Boutiques that live in that domain every day will beat me on technical depth there. I won't pretend otherwise.
You already know what's broken and you need a senior operator doing the work part-time for 6-12 months. That's not what a 6-week diagnostic gives you. Bolster, Continuum, Chief of Staff Network - they're built exactly for this.
If the role is genuinely permanent and you can find the right operator within your hiring timeline, hire. Consultants are bridges, not destinations. My job is to make myself unnecessary - sometimes that means pointing you toward the hire.
If your situation matches the left column, the next move is a free 30-min intro call.
Book the intro call
If you're not happy with the result, full refund. You judge the outcome, not me. No paperwork. No awkwardness. Just an email.
Stay small, fast, and stable - until you're truly ready to scale.
Transition into the AI era. Become faster, leaner, and more productive.
See past the deck. Know what you're really investing in.
Every company is shaped by the decisions its leaders make - the dozens of small judgments per day that compound into culture and results.
I build the layer underneath those decisions: executive thinking that stays clear under pressure, judgment that compounds with time. The organization downstream is productive, durable, flexible, innovative, and lean - by structure, not by accident.
10+ years leading tech products and teams in regulated environments. M.Sc in AI. 2+ years personally shipping AI-powered apps and automation - not just advising on them. The combination is rare: deep technical fluency, real change-management experience scaling R&D 30 to 150, and an operator's sense of where systems actually break.
My goal: deliver sharp assessments with practical recommendations your team can implement productively, durably, and at modern consulting economics.
Read My StoryLed teams from 30 to 150, built regulated banking infrastructure, shipped to 100K+ users. I know where systems break because I've built them.
M.Sc in AI plus 2+ years personally shipping AI-powered apps with Claude Code, RAG, and agentic workflows. I operate with AI daily - not just consult about it.
Organizations don't fail because of bad strategy - they fail because people resist change. I understand what drives behavior and how to shift it.
Long-form writing on AI transformation, scaling organizations, and operator-led consulting. The frameworks behind the work.
Insights on AI transformation, scaling organizations, and lessons from a decade inside regulated tech.
AI in business, high-stakes decisions, and practical scaling - talks that leave your audience with tools they can use tomorrow.
Book a keynote for your event. Run a workshop for your team. Or get ongoing consulting support. Let's find the right fit.