Build vs Buy in AI: When to Develop Custom and When to Hire SaaS

The short rule of build vs buy in AI: buy SaaS when the process is standard and you can adapt to how the tool works; develop custom when the process is your competitive advantage or touches systems that no SaaS covers well. In numbers: AI SaaS typically costs between €20 and €150 per user/month (or €300 to €3,000/month per platform), and custom development between €15,000 and €60,000 initially plus 15-25% annually for evolution. The trap is that an honest comparison isn't the first-year price, but the total cost over three years and who owns what at the end.

This article puts the numbers for each option side by side, the three-year calculation with a real example, and the criteria that truly decide—which are almost never the starting price.

The numbers for each option

Buying (AI SaaS)

• Tools per user: €20-60/user/month on standard plans and €60-150 on advanced plans with AI features. For 25 users, between €6,000 and €45,000/year.
• Platforms by volume: chatbots, document analysis, or packaged automation: from €300 to €3,000/month depending on volume and features, plus an initial setup of €1,000 to €10,000.
• Enterprise: annual contracts from €20,000 to €100,000+ with implementation, support, and SLA.

Advantages: you start in days or weeks, maintenance is included, and technical risk is low. Drawbacks: you pay forever, the price per user tends to rise with each renewal, and the process adapts to the tool, not the other way around.

Building (custom development)

• Agent for a specific process: €15,000-40,000 initial.
• Multi-system core process: €40,000-80,000.
• Evolution and maintenance: 15-25% annually of the initial cost, plus €50-500/month in model consumption.

The full breakdown by project type is in how much a custom AI agent costs. Advantages: the system follows your exact process, connects to your systems via native connectors, and the logic and data are yours. Drawbacks: higher initial investment, a timeframe of 4 to 10 weeks, and the need for a reliable provider or a capable team.

The three-year calculation, with an example

Imagine a team of 25 people evaluating a SaaS tool at €90/user/month versus a custom agent for €35,000.

• SaaS: 25 × €90 × 12 = €27,000/year. Over three years, €81,000—assuming the price doesn't go up, which it usually does. At the end of the three years: you keep paying and you own nothing.
• Custom: €35,000 initial + ~€7,000/year for evolution + ~€2,400/year for model consumption = about €63,000 over three years. At the end: the system is yours, and the marginal cost of subsequent years is a fraction.

The conclusion is not "custom always wins": with 5 users instead of 25, the SaaS would cost €16,200 over three years and would win clearly. The conclusion is that the crossover point depends on the number of users, the volume, and the horizon—and that you have to do the math with your numbers before deciding, not after.

One more nuance for a fair comparison: for SaaS, add the permanent manual work for what the tool doesn't cover and the cost of adapting your process to theirs; for custom development, add your team's time during the project and the risk of choosing the wrong provider. Neither figure appears on the rate card, and both carry weight.

When to buy

• The process is standard in your sector and doesn't differentiate you (signing documents, transcribing meetings, generic helpdesk).
• Few users or low volume: the monthly fee takes years to match a development cost.
• You need results in days and can adapt to how the tool works.
• You want to validate that the use case adds value before investing seriously: a SaaS is a cheap experiment.

When to build

• The process is your competitive advantage: how you qualify, how you buy, how you serve. Standardizing it with the same tool your competition uses is giving away your edge.
• The SaaS only covers 70%, and the remaining 30% condemns you to permanent manual work or twisting your operations.
• It touches several internal systems: deep integrations are the chronic weakness of SaaS.
• The volume makes the price per use of the SaaS clearly exceed the cost of operating something proprietary.
• Your data or regulation doesn't fit with the provider's conditions.

The third way, which is the standard: buy the standard, build the differential

In practice, almost no company is at an extreme. The healthy combination is to buy the layers that don't differentiate you (office software with AI, transcription, team tools) and build the layer where your advantage lives: the agents that execute your processes with your data over your systems. This budget distribution—how much for tools, how much for development, how much for training—is developed in how companies should invest in AI.

The traps of each path

The "buy" trap: silent dependency. Three years later you have twelve subscriptions, your data spread across twelve places, prices rising with every renewal, and an operation that no one on your team can explain. Before signing, look at the exit clause: who owns the data, in what format does it come out, and what does it cost to leave?

The "build" trap: reinventing wheels. Developing a custom solution for what a SaaS solves for €100/month is technical vanity, and underestimating maintenance is the most common calculation error: custom software without an evolution budget degrades just like an unpaid subscription, only slower and without warning.

If you have the decision in front of you and it's not clear which side your case falls on, our diagnosis does exactly that math: what to buy, what to build, and in what order, with your operational numbers.

Frequently Asked Questions

Which is cheaper in the long run, SaaS or custom development?

It depends on users, volume, and horizon. As a reference: with teams of 15-25 people and intensive use, custom development usually crosses with SaaS between the second and third year; with small teams or light use, SaaS almost always wins. The calculation must be done over three years, not one.

Can I start with SaaS and move to custom later?

Yes, and it is usually a good strategy: the SaaS validates that the use case adds value and teaches you what you truly need. The requirement is not to have your data held hostage: verify from the start that you can export it in a usable format.

And building with no-code tools, isn't that the best of both worlds?

For simple automations and validating ideas, yes: it's fast and cheap. Its limits appear with volume, exceptions, and deep integrations, and platform dependency in no-code is as real as in any SaaS. It is a useful middle point, not a magical third category.

How do I evaluate provider dependency before signing?

Three questions for the contract: who owns the data and configuration if you leave, in what format can you export them, and what price hike history does the provider have. If the answers are vague, the real price of the tool is higher than the rate card.