What comes after SaaS.

Software as a service was born from an assumption: building software was so expensive that the only way to make it affordable was to build a single product and sell it to thousands of organizations. They accepted the deal: cheap, instant software, in exchange for working the way the software dictated.

For two decades that deal paid off. Not anymore, for three reasons.

The only alternative to SaaS was commissioning custom development: expensive upfront, slow, and frozen on delivery day. Between the two paths sat most small and medium-sized businesses, getting by with what they have: answering WhatsApp by hand, confirming appointments one by one, copying data between systems that do not talk to each other, and relying on someone on the team to remember everything.

TMaaS will replace SaaS.

If building and changing software costs a fraction of what it used to, there is no longer any reason for every organization to use the same software. Each one can have its own system, made for its operation, that evolves continuously.

With TMaaS, an organization no longer buys a closed product or commissions a project with an end date. It has a system built for its operation, running in its own installation and changing as the organization changes. It gets the continuity of a service, as with SaaS, but cut to its measure, as at a tailor's.

The name takes the structure of Software as a Service and changes one word. What is delivered as a service is no longer the same software for everyone, but software tailored to each organization.

What it replaces and what it does not

TMaaS replaces application SaaS: the CRM, the scheduling tool, the customer service inbox and the management software that force organizations to work their way. Infrastructure services, such as payments, messaging, cloud or the AI models themselves, remain shared building blocks. A TMaaS system is built on top of them.

Custom development always had a cost problem, not a value problem. What was expensive was the work: programming, testing, documenting and maintaining.

AI coding agents changed that equation. A small team of people working with AI builds in days or weeks what used to take months, and changes in hours what used to require a new project.

This has three consequences:

1. A system of your own stops being a luxury. What only large organizations could have is now within reach of any organization, however small.
2. Changes stop being projects. Modifying a system costs so little that it can be done continuously, as the organization changes.
3. The bottleneck moves. It is no longer writing code, but understanding each organization well, deciding what to build and taking responsibility for what reaches production.

That is the advantage SaaS cannot match. Its model depends on every organization using the same thing. When making something different for each one costs little, settling for the generic no longer makes sense.

In TMaaS, human work focuses on understanding, deciding and taking responsibility. AI does the rest.

Seven principles set TMaaS apart from SaaS and from traditional custom development.

1. I

   Software adapts to each organization

   Each organization's rules, how it serves, charges, confirms or refers, are the starting point. They are not a configuration option inside someone else's product.

2. II

   Common base, tailored layer

   Each system is built on a proven, shared base; what is specific to each organization lives in a separate layer. Without a common base, the model is an agency by another name. Without a tailored layer, it is just another SaaS.

3. III

   One installation per client

   Each organization runs in its own environment, with its data kept separate. What changes for one does not affect another.

4. IV

   The system evolves with the organization

   A TMaaS system is not delivered and then frozen. It changes continuously, at the pace of the operation it serves.

5. V

   Data belongs to the operator

   The information an operation generates belongs to the organization that generates it, not to whoever builds the system.

6. VI

   People who answer, AI that builds

   AI programs, tests and documents. People understand each organization, make decisions and approve what reaches production. Someone is always accountable.

7. VII

   Measure before and after

   Each system starts with a baseline of the indicators it aims to move. That makes it possible to check whether the tailored system outperforms the generic software it replaces.

TMaaS takes the best of the two traditional paths: the continuity of SaaS and the fit of custom development. It leaves behind the worst of each: the rigidity of the first and the obsolescence of the second.

A TMaaS system does not end at delivery. Its construction repeats for as long as the organization uses it.

After step 3, everything is measured again and the cycle starts over.

A TMaaS system has layers. The lower the layer, the more it is shared; the higher, the more specific to each organization.

The rule that makes the model work: whatever is built for one organization, if it serves others, moves up into the sector modules or the common base. That way, each new system is built faster than the last.

This is a draft thesis. These questions do not have a definitive answer yet.

1. How quickly will organizations leave their current SaaS, and what holds the change back: contracts, data or habit?
2. How will the big SaaS players respond: by opening their products to customization, or by losing ground to new systems?
3. Where is the line between a tailored adjustment and a new product?
4. How far will AI reduce the human work needed to understand and maintain each system?
5. At what point does a group of organizations in the same sector become, in effect, a vertical SaaS?