Data in, model out
How every engagement starts, before a single number is built
Built for high-stakes decisions
Deal materials built for the funds and founders who can't afford to get the numbers wrong.
One weak assumption is all it takes
Investors spot it in minutes. One number that doesn't tie, and the whole case is suspect. So we build it from the ground up.
Foundation
Narrative
Delivery
Work that survives a committee
The model that runs the numbers, the memo that makes the case, and the independent review that pressure-tests both.
Levered equity cash flow
Three cases through hold · equity above water by Year 3
BaseDownsideUpside
Returns summary
5y hold · refi Yr 3
UnlevLev
IRR
MOIC
Payback3.1y
Exit EV$370M
Transaction summary
| Enterprise value | $1,850.0 |
| Equity value | $620.0 |
| Total debt | $1,230.0 |
| Cash | $20.0 |
| Net debt | $1,210.0 |
| Entry EV / EBITDA | 10.2× |
| Net debt / EBITDA | 6.7× |
| IRR | 24.3% |
| MOIC | 2.5× |
Revenue & EBITDA · $M
| Year | 2025A | 2026E | 2027E | 2028E | 2029E |
|---|---|---|---|---|---|
| Revenue | 245 | 268 | 294 | 324 | 356 |
| % growth | — | 9.4% | 9.7% | 10.2% | 9.9% |
| EBITDA | 72 | 83 | 94 | 108 | 124 |
| % margin | 29.4% | 31.0% | 32.0% | 33.3% | 34.8% |
Leverage profile · Net debt / EBITDA
Sources & uses
| Senior debt | $890.0 |
| Subordinated debt | $340.0 |
| Equity | $620.0 |
| Total sources | $1,850.0 |
| Purchase price | $1,830.0 |
| Fees & expenses | $20.0 |
| Total uses | $1,850.0 |
Returns summary
| IRR | 24.3% |
| MOIC | 2.5× |
| Equity multiple | 2.5× |
| Payback | 4.2y |
Sensitivity · IRR %
| Exit \ Entry | 9.0× | 9.5× | 10.0× | 10.5× |
|---|---|---|---|---|
| 10.0× | 21.8 | 19.6 | 17.5 | 15.6 |
| 11.0× | 28.4 | 26.0 | 24.3 | 22.1 |
| 12.0× | 34.1 | 31.6 | 29.2 | 27.0 |
DashboardAssumptionsP&LBalance SheetCash FlowDebt ScheduleReturns
Executive summary
The opportunity at a glance
We are acquiring a high-quality, market-leading software business with durable growth, strong margins and multiple levers to accelerate value creation. The investment offers an attractive risk-adjusted return profile with clear downside protection.
Target
Vertical SaaS platform
Sector
Software
HQ
North America
Enterprise value
$1,250M
Revenue (LTM)
$312M
EBITDA margin
28%
Transaction
Buyout
Investment size
$450M equity
Close
Q3 2025
Company overview
A market leader with scale and stickiness
Leading provider of mission-critical software for mid-market and enterprise customers.
3,200+ customers with 90%+ recurring revenue and 119% net revenue retention.
Highly integrated product with high switching costs and long customer relationships.
Expanding TAM driven by digitization and industry tailwinds.
Customers
3,200+
NRR
119%
Recurring
91%
LTV / CAC
5.4×
Investment thesis
Why we are investing
1
Durable organic growth
Strong product-market fit and secular tailwinds.
2
Attractive unit economics
High gross margins and efficient go-to-market.
3
Scalable platform
Multiple vectors for expansion and automation.
4
Proven management team
Experienced leaders with a track record of execution.
Capital structure
Pro forma at close
$1,250M
Enterprise value
Senior Term Loan B$650M52%
Unitranche / Mezz$150M12%
Equity$450M36%
Key metrics (at close)
Net debt / EBITDA5.2×
Interest coverage3.4×
Cash interest rate8.2%
Equity check size$450M
Key risks
Top risks and mitigants
Macro slowdown impacting growth
Mitigated by recurring revenue and a diversified base.
Competition and pricing pressure
Mitigated by product differentiation and switching costs.
Execution on value creation plan
Mitigated by an experienced team and a clear plan.
Talent retention
Mitigated by incentives and a culture of ownership.
Refinancing risk
Mitigated by strong cash flow and conservative leverage.
Executive summary of findings
What it means
8 high-priority issues
Could materially impact valuation, returns or the decision.
$29.4M total value impact
Aggregate impact to enterprise value from the recommended changes.
Model logic is sound
Robust structure with clear assumptions and logical flow.
Transparency is good
Inputs and calculations are well-documented and easy to follow.
Findings by severity
Breakdown of issues · 30 total
8
12
10
Redline: key changes & corrections
Track record of all material adjustments
| Sheet | Item / description | Issue | Original | Revised | Delta | Impact | Priority |
|---|---|---|---|---|---|---|---|
| Revenue | FY26 growth rate | Growth > market without support | 22.0% | 15.0% | (7.0%) | ($12.4M) | High |
| Revenue | Churn rate | Below historical range | 3.0% | 5.0% | 2.0% | ($4.7M) | High |
| COGS | Gross margin | Inconsistent with unit economics | 82.0% | 78.5% | (3.5%) | ($6.1M) | High |
| Opex | S&M % of revenue | Below peer benchmark | 8.0% | 10.5% | 2.5% | ($3.2M) | Med |
| Tax | Effective tax rate | Static rate not supportable | 21.0% | 24.5% | 3.5% | ($1.8M) | Med |
| Debt | Interest rate | Below market for leverage level | 5.0% | 6.5% | 1.5% | ($1.2M) | Med |
| Capex | Maintenance capex | Not tied to revenue growth | $10.0M | $14.0M | $4.0M | ($4.0M) | Low |
| WC | DSO | Days below historical | 30 | 38 | 8 | ($1.0M) | Low |
Audit checklist
Key areas reviewed
Structure & logicPass
Inputs & assumptionsFail
Calculations & linksPass
Financials & outputsReview
Formatting & usabilityPass
Consistency & integrityReview
Recommendations
What we suggest
- Align revenue growth with market benchmarks and historical performance.
- Reassess churn and pricing assumptions to reflect current trends.
- Update margin and opex assumptions to be in line with peers.
- Tie working capital and capex to operational drivers.
- Stress-test the downside case using more conservative scenarios.
Screen Data Room
Running screening…
- Indexing 214 documents
- Identifying missing documents
- Executing the 47-question battery
- Isolating red flags
- Tracing answers to source…
Draft IC Memo
Work in progressWIP
Drafting memo…
- Applying the fund's template
- Importing verified findings
- Ranking findings by materiality
- Referencing every claim
- Preparing draft for review…
Refresh Comps
Work in progressWIP
Refreshing comps…
- Retrieving latest filings
- Extracting reported metrics
- Rebuilding the peer set
- Updating 142 linked cells
- Reconciling to source…
Financial workflows, engineered
Encode institutional knowledge into every decision, so each deal makes the next one sharper. Cited to source, verified by hand, run inside your stack.
Two practices. One standard.
Deal materials built by hand, and AI systems built into your stack. Two ways of working, held to the same bar. Every number traces to a source. Every claim survives the room it's read in. Nothing ships on autopilot: a human verifies the work before it reaches you.
Every asset class is judged on different numbers
Five sectors, each judged on its own numbers. Every deliverable is built around the drivers that actually move the deal at hand.
Real Estate & Development
- Development costs, phased cash flow
- Rent, lease & operating structures
- Debt vs. equity modeling & IRR logic
Infrastructure & Energy
- Project finance & multi-tranche debt
- Concession, offtake & availability terms
- DSCR, cash sweeps & refinancing
SaaS & Subscription Businesses
- Recurring revenue, cohorts & net retention
- ARR build, churn & expansion logic
- Rule-of-40, CAC payback & burn multiple
eCommerce & Manufacturing
- COGS, inventory & working-capital cycle
- Channel mix, AOV & repeat-purchase
- Capacity, throughput & gross-margin bridge
Healthcare & Regulated Markets
- Reimbursement & payer-mix modeling
- Approval gates & phased commercialization
- Compliance-driven cost & risk overlays
Trained where the capital is real
Institutional deal exposure. The models and memos behind deals that shaped real capital allocation.
$2B+
Deal workflowLive institutional deals
4 yrs
Modeling experienceIB · PE · Structured Finance
1000+
Hours of AI trainingIB workflows
Straight answers
The questions investors and founders actually ask before they engage.
Deal materials, built by hand. Institutional-grade financial models (LBO, M&A, DCF valuation, project finance, real estate, infra), investment-committee memos and independent reviews of models you already have.
AI systems, built into your stack. The second practice: workflows that run the same work inside your own infrastructure, starting with data-room screening: every answer cited to source and verified by hand.
Funds, family offices, independent sponsors and founders. Anyone who needs numbers that hold up in front of an IC, an LP or a board.
Same institutional standard, without a big firm's lead times, layers or rigid scope. Direct access to $2B+ of live-deal expertise, fast turnaround, and work that flexes to exactly what you need.
Yes. Independent model reviews are a core service. I pressure-test your logic, find what breaks, and hand back a defensible, audit-ready version with every change documented.
A short brief and whatever you have: a CIM, financials, a data room, even a rough sketch. We scope it on a 30-minute call and lock the deliverable, timeline and fixed fee before any work begins.
Usually a few days to a week, depending on the scope and how urgent it is. The exact timeline is fixed up front, before any work begins.
Yes. Works can run under NDAs, and deliverables can be white-labeled to your template so it ships as your own.
No. Never. Nothing you share is used to train any model. Systems can run in your own cloud, every engagement works under NDA, and your documents stay yours.
Fixed fee per engagement, agreed before any work starts. No hourly surprises. Revisions are included until the model ties and the committee's satisfied.
Ready to put real numbers behind it?
Book a 30-minute call and leave with a clear scope, timeline and fixed fee. No obligation.