Get the 18 month cost projection in writing before signing.
Ask the vendor to model the total cost at your projected headcount for month eighteen, twenty four, and thirty six. If they will not, that is your answer.
Primer
Build versus buy AI: stop comparing demos. Compare costs at month 18.
Every SaaS AI demo is impressive in week one. The interesting question is what does it look like in week 78. By then, your team has grown, your data has changed, and the per seat price has compounded. Run those numbers before signing.
The hook
Where this shows up.
A vendor pitch deck shows a feature matrix and a per seat price. The feature matrix is what the tool can do this quarter. The per seat price is what you pay this month.
Neither answers the actual question, which is what does this cost over the lifetime you intend to use it. The four costs that determine the answer are not on the deck.
The misconception
That you should compare features at the demo.
What most people believe
Features are easy to demo and easy to ship. The vendor will catch up to whatever gap you point out within a quarter or two. Feature comparison at month one is a terrible predictor of fit at month eighteen.
What is not easy is changing the underlying economics of a SaaS deployment after you have committed. Per seat pricing scales linearly with team growth. Data lock in compounds. Customization debt accumulates. These are the variables to compare.
The better model
Compare four numbers at month 18.
What actually works
Take your current team size, project realistic growth, and run the math. The cloud tool that is cheaper in month one is often more expensive in month eighteen. Here are the numbers vendors leave off the deck.
- 01
Per seat cost extrapolated to your team size at month 18.
A 25 person team at $49 per seat per month is $14,700 per year. Grow to 40 seats and it is $23,520 per year. SaaS pricing rewards customers who do not grow.
- 02
Data egress cost when you switch.
How does your data come out? Is the export complete or partial? Is there a fee? How long does it take? If the answer is unclear, assume hostage pricing when you try to leave.
- 03
Customization tax.
You are paying for every feature in the suite, including the ones your team will never use. Inventory the features you actually need. If it is three of forty, question whether you are buying a tool or a packaging job.
- 04
Lock in cost when you migrate.
Workflows built inside a SaaS tool do not transfer to the next one. The cost of rebuilding them shows up only when you decide to leave. Estimate that cost before signing, not at the moment you want out.
Three decisions
Make these calls differently this week.
Test the export path before subscribing.
Ask for a test export against a sample dataset. Look at the file format, the completeness, and the time to receive it. A tool that hides its export path is a tool that has decided you will not be leaving.
Plan your exit before your entry.
Write the migration plan on day one. What would it take to move to a different tool, or to a custom build, in three years? If the answer is rebuild from scratch, factor that into the price.
How ByteWorthy uses this
What this looks like in our work.
Custom AI you own. Not SaaS you rent. That is our thesis, and it shapes every build we take on. We do not always recommend custom. For a small team with non sensitive data and unpredictable usage, SaaS is often the right call.
For a healthcare practice with thirty staff, sensitive data, and a five year horizon, custom usually wins on cost alone within eighteen months. The math tells the story. We are happy to run it with you.
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