Momentum
Buyers see a streak, not a snapshot.
Exit-Prep Operational Readiness
For businesses ($2M–$30M revenue) heading to sale in the next 1–3 years where the team still runs on manual workflows.
XLev installs the AI-powered operations, reporting, and workflows that move businesses from a 3× to a 5× multiple — before you go to market.
Australia-based · Working with businesses preparing for sale globally
The Problem
When a buyer inspects a business, they reduce the price for operational reasons — not just financial ones.
If you leave, key relationships and knowledge leave with you. Buyers price that risk.
Fragile, expensive, and hard to scale. Manual work signals hidden cost and key-person risk.
Buyers need to see the pipeline. Missing data forces them to rely on your word — which increases risk.
If you can't show buyers how the business runs, they assume it runs badly.
Due diligence takes longer. Confidence drops. The price follows.
Revenue leaks that buyers will model into their bid — whether you know about them or not.
The Solution
We systematise the workflows, knowledge, and decisions that currently depend on you.
We build the reporting and dashboards that give buyers confidence in how the business runs.
We automate the high-friction manual work that makes buyers nervous about scalability.
We document, measure, and report the operational improvements — so buyers see proof, not promises.
XLev does not provide M&A advisory, legal, financial or valuation advice. We improve operational systems — the layer underneath the numbers.
The Math
Buyers price businesses two ways at once: the multiple they're willing to pay, and the discounts they apply on top. We work on both — at the same time, before the sale process starts.
Founder-led businesses typically transact at 2.5–3.5× EBITDA. Operationally mature businesses of the same size routinely transact at 4.5–6×. The gap is operational risk — not financial performance.
Every reason a buyer chips the price is an operational gap we can close before the process starts.
Indicative ranges drawn from published M&A practitioner guidance (IBBA, Pepperdine PCMS). Actual impact varies by sector and deal.
Documented systems, not founder memory.
Dashboards, SOPs, and an evidence pack ready for DD.
Proof the business scales without proportional headcount.
Illustrative only. Not a valuation. XLev does not provide M&A, legal, financial or valuation advice. Multiples shown are indicative ranges from published M&A research; outcomes depend on sector, buyer pool, and deal structure.
On a deal like this, our entire engagement is roughly 1–2% of the uplift it's designed to create.
See how we'd do it for your businessThe proof compounds
We don't sell promises. We track the streak — workflows shipped, hours given back, multiples earned — and put it where you and your buyer can both see it.
Buyers see a streak, not a snapshot.
Average client multiple on fees, month 6.
24-month projected wage equivalent saved.
"This isn't a pitch deck. It's the dashboard your team will actually log into."
See it inside XLev Lab ↓The Process
We run a structured Operational Readiness Assessment across 8 dimensions. You get a scored report showing exactly where buyer risk sits — and what to fix first.
We install AI-powered operating systems that reduce owner dependency, clean your data, systemise your workflows, and surface the reporting buyers need to see.
Everything is tracked inside XLevLab — your client portal. Live metrics, before/after data, system performance, and operational improvement evidence.
We stay on retainer through the sale process. Supporting due diligence, maintaining systems, and making sure the operational story holds up under scrutiny.
Introducing XLev Lab
XLevLab is the client portal that comes with every XLev engagement. One login. Everything in one place.
Your AI systems running in real time. Workflow stats, success rates, and operational metrics.
Industrial fabrication · 84 staff · $18–25M revenue · Target sale Q4 2027
Who We Work With
XLev works with businesses doing $2M–$30M in revenue, 10–80 staff, planning a sale in the next 6–36 months. If your team still runs on manual workflows and the operational story isn't ready for due diligence — this is where we start.
Investment
On a $5M sale, our full engagement is typically 1–2% of the transaction. The uplift it's designed to create is measured in multiples of that — see The Math for the worked example.
$4,500 – $7,500
A structured 10-day diagnostic across 8 operational areas. Produces the Readiness Report — your buyer risk map.
10 business days
Designed to identify uplift worth multiples of its cost.
$35,000 – $85,000
Comprehensive operational overhaul. AI systems, reporting, documentation, and evidence — all built before the sale process starts.
8–16 weeks
Designed to return 10–25× its cost on a typical exit.
$5,000 – $12,000/month
Stay-on support through the sale process. Due diligence assistance, system maintenance, and operational evidence.
Rolling — typically 6–12 months
Designed to protect the uplift through due diligence.
All fees exclude GST. XLev does not charge success fees or take a percentage of the sale.

Tom Downie
Founder · XLev
Who You're Working With
I built XLev after running a five-campus education business in Sydney for ten years. To scale it without scaling the team, I built our own AI infrastructure — payroll automation, student retention systems, management dashboards, and operational workflows. It worked. XLev brings that same capability to businesses preparing for sale.
I'm not a consultant who presents a report and disappears. I build the systems, train the team, and stay through the process — because the operational story needs to hold up when a buyer tests it in due diligence, not just when it looks good in a deck.
XLev works with a small number of businesses at a time. Every engagement gets my full attention.
Location
Sydney's Northern Beaches, NSW
Background
Founder of Better Tuition Academy (est. 2015, 5 campuses, 455 students)
Tell us about your business and timeline. We'll reply within one business day with an honest read on whether we can help — and what the starting point looks like.
tom@xlev.ai · xlev.ai · Sydney, Australia