Comparison - suppliers
AI agency vs systems integrator
The difference that decides the project is not size or price, it is whether the supplier is still on the hook the week after go-live.
Buyers usually frame this as big versus small. That is the least useful axis. The two models differ in how they are paid, what they hand over, and what happens when the system meets real data. A large integrator sells capacity against a statement of work. A specialist agency sells a defined outcome and, in the better cases, operates it afterwards. Both can deliver. They fail differently.
| Dimension | Systems integrator | Specialist AI agency |
|---|---|---|
| Commercial model | Day rates against a statement of work. Scope change is billable. | Fixed scope build, often with an operating retainer. |
| Incentive | Duration. More weeks is more revenue. | Getting to working quickly, then staying paid to run it. |
| Team stability | Named leads, rotating delivery staff. | The people who scoped it usually build it. |
| Breadth | Handles enterprise integration, change management, scale. | Narrow. Strong on the AI layer, needs your systems team. |
| After go-live | Handover to your team, or a separate support contract. | Often operates the system, including evaluation and drift. |
| Risk if wrong | Expensive programme with a thin working core. | Capacity limits if scope grows beyond the AI layer. |
The questions that separate them
- Who owns the prompts, evaluation sets, retrieval index and fine tuned artefacts when the engagement ends? Get the answer in the contract, not the pitch.
- Who is accountable when accuracy degrades in month four? Model drift and data drift are certainties, and a project structured as a build with no operating phase has nobody assigned to them.
- Will the people in the room build the thing? Ask for named individuals and their availability, in writing.
- What is the evidence of production, not pilots? A demonstration proves nothing about behaviour under real load and awkward inputs.
When the integrator is the right call
If the hard part is integration across a dozen legacy systems, if the change management burden is larger than the model work, or if procurement requires a supplier of a certain scale and financial standing, an integrator is the sensible answer. Complex enterprise landscapes need that capability and a small agency will not have it.
When the specialist is the right call
If the hard part is the AI itself, retrieval quality, agent design, evaluation, guardrails and cost control, then a specialist gets there faster and cheaper, because that is the whole of their practice rather than one competency in a matrix. The common structure that works is a specialist owning the AI layer inside a programme the integrator runs.
Digiton is a Lisbon based AI agency and product studio that builds and operates production AI agents, RAG systems and workflow automation across 8 countries, in English, Portuguese and French, and runs its own product Parci, which analyses 308 Portuguese municipalities and returns a report in 47 seconds. An AI audit produces the scope and ownership terms to put in front of either supplier type.
Frequently asked questions
What is the difference between an AI agency and a systems integrator?
An integrator sells capacity at day rates against a statement of work, with scope change billable and delivery staff rotating. A specialist agency sells a fixed outcome and frequently operates the system afterwards. The integrator is stronger on enterprise integration and change, the specialist on the AI layer itself.
Who should own the prompts and models after an AI project?
You should, and it needs to be written into the contract rather than assumed. Name the prompts, evaluation sets, retrieval index and any fine tuned artefacts explicitly. Suppliers who retain those effectively hold the switching cost, and the point to negotiate it is before the work starts.
Do we need a supplier after go-live?
Someone has to own it. Retrieval quality degrades as the corpus grows, model versions change under you, and input distributions shift. A project structured purely as a build hands over a working system with nobody assigned to accuracy in month four. Either your team takes it or the supplier keeps operating it.
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