How we compare
Two questions come up in almost every conversation: how is a purpose-built agent team different from an AI platform, and how is sovereign, on-premise AI different from a SaaS LLM. Here is the honest comparison.
Purpose-built agent team vs configurable AI platform
| Purpose-built agent team (Cultivator AI) | Configurable AI platform | |
|---|---|---|
| What you get | A team of specific agents shaped to your workflow | A toolkit you configure into your workflow |
| Who does the modelling | We do, around your data | You do, into the platform’s model |
| Interface | Each agent is both the logic and the interface | A generic UI you adapt |
| Time to value | Deploy the agents you need | Configure, integrate, then maintain |
| Where it runs | Your infrastructure, EU compute | Often the vendor’s cloud |
| Lock-in | You own the agents | Tied to the platform |
| Best when | You want a specific job done well | You want a horizontal tool to build on |
Sovereign, on-premise AI vs SaaS LLM
| Sovereign on-premise (Cultivator AI) | SaaS LLM | |
|---|---|---|
| Data path | Stays on your servers | Sent to the vendor |
| Compute location | Your infrastructure, in the EU | The vendor’s regions |
| Third party in the data path | None | The LLM vendor |
| Cost model | Small open-source models on your hardware | Per-token API pricing |
| EU data residency | By design | Depends on the vendor |
| Control | You own the models and the infrastructure | The vendor controls both |
Not sure which side of the table you need?
Tell us the workflow. We will be honest about whether a purpose-built agent team is the right fit, and what it would look like.
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