Places Of Interest

Financial Model for AI-agentic SaaS Businesses

An AI Agentic SaaS business delivers its product as cloud‑based software (the familiar SaaS model) but the “product” is an autonomous or semi‑autonomous agent system that can plan, decide and act on the customer’s behalf across many tools and data sources, not just return a chat response.

In other words, the value proposition shifts from “software that lets you do the work” (classic SaaS) to “software that does the work for you and reports back. I've built this simple financial model to look at the economics of operating such a business. It is similar to the 'function-as-a-service' business model.

Example Business Plan Scaling Multiple Driving Ranges

Below is a worked‑example business plan for rolling out four modern, technology‑enabled golf‑driving ranges over a five‑year horizon. Numbers are rounded to the nearest $100 k where appropriate and should be adjusted to local market realities (land cost, labor rates, tax, etc.). The structure is designed so you can drop it straight into a spreadsheet model and refine each module.


You can plug your own assumptions into this driving range financial model and plan various scenarios.

1. Roll‑out & development schedule (“Use of time”)

Calendar yearQuarter focusKey milestonesSites in operation EoY
Year 0 (Pre‑launch)Q1‑Q4• Secure master lease on first parcel
• Finalise brand/tech stack (Toptracer, ball dispensers, POS)
• Raise seed equity ($6 m)
0


Year 1
Q1‑Q2Construct & fit‑out Site #1 (60 bays)
Q3Soft opening Site #11


Year 2
Q1Close senior debt facility ($8 m)
Q2‑Q4Build & open Site #2 (75 bays)2


Year 3
Q2Build & open Site #3 (75 bays)3


Year 4
Q2Build & open Site #4 (90 bays)4


Year 5
Q1‑Q4Operate portfolio, prepare exit or dividend recap4

2. Capitalisation

ItemUnit costCountTimingTotal
Land leasehold pre‑payments & legal$0.30 m4Yr 1‑4$1.2 m
Site construction & fit‑out$3.00 m4Yr 1‑4$12.0 m
Technology package (ball‑tracking, POS, screens)$0.20 m4Yr 1‑4$0.8 m
Pre‑opening marketing & training$0.15 m4Yr 1‑4$0.6 m
Total project cost$14.6 m

Funding mix
  • Equity: $6.0 m (ordinary, 70 % investor / 30 % founder)

  • Senior term loan: $8.4 m @ 6 %, 10‑yr amortisation (first draw in Year 1)

  • Working‑capital revolver: $1.0 m undrawn at close (not modelled in returns)


3. Operating model – per site at stabilisation (Year 3 of each site)

DriverAssumptionCommentary
Bays60–90mix by site size
Utilisation (sold bay‑hours ÷ possible bay‑hours)50 % average10 h trading day × 360 days
Average bay‑hour price$35dynamic pricing weekdays / weekends
Range revenue$3.78 m60 bays example
Food & beverage (F&B) attach30 % of range rev.Bar, casual dining, events
Total gross revenue$4.91 m
COGS – F&B35 % of F&B salesindustry norm
Fixed & semi‑variable op‑ex$1.82 m p.a.Labour ($1.05 m), rent ($0.40 m), utilities ($0.15 m), maintenance ($0.10 m), marketing ($0.12 m)
Site EBITDA$2.69 m~55 % margin

Ramp profile (share of stabilised revenue)
Year of operation1st2nd3rd+
% of stabilized rev.65 %85 %100 %

4. Portfolio‑level projections


Fiscal year
Sites open    Revenue ($ m)EBITDA ($ m)Maint. capex ($ m)Free cash flow ($ m)
113.21.10.11.0
227.43.00.22.8
3312.35.50.35.2
4417.27.90.47.5
5418.99.20.48.8

Includes 3 % annual inflation on fixed operating costs.

5. Investor return case

ItemAssumption / result
Equity invested (drawn Yr 1‑4)$6.0 m
Net debt outstanding at exit (post amortisation)$5.3 m
Portfolio EBITDA in Year 5$9.2 m
Exit multiple (market comps)6.0 × EBITDA
Gross enterprise value$55.2 m
Transaction & advisory fees5 %
Equity proceeds at exit (Yr 5)$48.4 m
Equity multiple (MOIC)8.1 ×
5‑year pre‑tax IRR≈ 52 %

6. Sensitivity checkpoints

Variable10 % downsideBase10 % upsideComment
Stabilised utilisation45 %50 %55 %High impact on revenue; watch weather seasonality
Exit multiple5.0 ×6.0 ×7.0 ×Depends on capital‑market conditions
Build cost / site$3.9 m$3.5 m$3.2 mConstruction inflation, scope creep
Wage inflation p.a.5 %3 %1 %Tight labor market risk

7. Next steps to turn this into a full model
  1. Layer in tax, interest and principal schedules to convert EBITDA to levered free cash flow.

  2. Allocate corporate overhead (HQ salaries, ERP, insurance) as a separate cost centre.

  3. Add seasonality sheet (monthly utilisation, weather index) – you already build these for Amazon products; the logic is similar.

  4. Scenario manager: create toggles for number of sites, bay count and pricing strategy.

  5. Investor waterfall (preferred return, promote) if raising institutional equity.


Take‑away

This illustrative plan shows that, with disciplined build costs and an early focus on high‑margin F&B, a regional portfolio of four tech‑enabled driving ranges can yield $9 m+ EBITDA and >50 % IRR to equity over five years. The key drivers to monitor are utilization, wage pressure and cap‑ex control; modest changes here swing returns materially, so model them in detail before capital is committed.

If you want help putting your own scenario into a spreadsheet model, I can help here.

Also, check out the Super Smart Bundle where you can instantly download over 200 unique financial model templates built by me over the last decade.

Article found in Startups.

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Example Business Plan for a 120-key Hotel

Below is a full‑length illustrative business plan for a ground‑up, 120‑key, upscale select‑service hotel located in a mid‑size U.S. metropolitan market. These assumptions are arbitrary, you can adjust as it fits your situation.