GDPR-compliant AI platforms compared
Which AI platform fits your requirements for data protection and control? A fair, factual comparison of AIgent, ChatGPT Enterprise, Microsoft Copilot and on-premise options against the criteria that really matter.
The market for AI tools has become hard to navigate. Almost every provider advertises data protection, but the differences are in the detail. This comparison places four common approaches side by side: the sovereign agent platform AIgent, ChatGPT Enterprise by OpenAI, Microsoft Copilot, and self-operated on-premise solutions. The goal is not a ranking, but an honest comparison so you can align the choice with your own requirements.
In short: GDPR compliance is not a seal but a question of data residency, third-party access and traceability. ChatGPT Enterprise and Microsoft Copilot, as offerings of US companies, remain generally subject to the US Cloud Act, while pure on-premise solutions demand considerable in-house effort. AIgent combines Swiss or your own infrastructure with model choice per agent and a complete audit trail.
Why the comparison is not trivial
The four approaches do not solve exactly the same problem. ChatGPT Enterprise and Microsoft Copilot are primarily assistants: they help individuals write, research and summarise. AIgent is an agent platform: here agents are configured to carry out multi-step tasks with vetted tools. On-premise solutions, finally, are more of a toolkit than a product. Anyone comparing them should keep this different orientation in mind.
What GDPR compliance really means
The term "GDPR-compliant" is used inflationarily but says little on its own. Compliance is not a seal a product receives once, but the result of technology, contracts and operation. A platform can create the preconditions, yet the company that uses it remains responsible. What matters, therefore, is how easy a platform makes it for you to actually prove your own compliance.
Three factors weigh particularly heavily: the location of processing, the question of third-party access, and the traceability of every processing operation. A platform that keeps data in Switzerland or in-house, regulates access clearly and logs every step shifts the burden of proof from a laborious special case to a documented normal case. This is exactly what the following approaches can be measured against.
The criteria that matter
In practice, six criteria decide whether a platform fits your data protection and control goals:
- Data residency: Where is data stored and processed?
- US Cloud Act: Is the operator subject to US jurisdiction?
- Agent over chat: Are tasks automated or only answers generated?
- Model choice: Can the model be set per use case?
- Audit trail: Is every step logged and traceable?
- Pricing model: Per seat, usage-based or as a licence?
The comparison at a glance
| Criterion | AIgent | ChatGPT Enterprise | Microsoft Copilot | On-premise (self-operated) |
|---|---|---|---|---|
| Data residency | Switzerland or your own infrastructure, up to air-gapped | OpenAI cloud, EU data residency partly available | Microsoft cloud, EU Data Boundary available | Entirely your infrastructure |
| US Cloud Act | Not affected with Swiss hosting or on-premise | US company, generally affected | US company, generally affected | Not affected |
| Agent over chat | Agents with vetted tools, no-code builder | Chat assistant, increasingly agentic features | Assistant in Office, agents via Copilot Studio | Freely buildable, but in-house development |
| Model choice | Per agent: on-premise, Swiss or international | OpenAI models | Primarily OpenAI models via Azure | Open models of your choice, self-hosted |
| Audit trail | Every step logged: model, tool, cost | Admin logs and logging | Logging via Microsoft Purview | To be implemented yourself |
| Pricing model | Cloud: Standard/Plus seats with an included usage allowance. On-premise: fixed organisation licence; implementation and infrastructure priced separately. | Per seat and month | Per seat and month, plus M365 | Infrastructure plus engineering effort |
ChatGPT Enterprise
With ChatGPT Enterprise, OpenAI offers powerful models, a polished interface and, in the enterprise version, the commitment not to use inputs for training. For many assistance tasks the product is first-rate. From a sovereignty perspective, however, OpenAI remains a US company and is therefore generally subject to the US Cloud Act, even if data residency options limit the storage location. Model choice is restricted to OpenAI's offering.
Microsoft Copilot
Microsoft Copilot scores through tight integration with Microsoft 365. Data stays in the tenant, the EU Data Boundary regionally limits processing, and Microsoft Purview provides an established tool for logging and governance. Copilot Studio also allows you to build agents. As with OpenAI, though, Microsoft is a US corporation, so the Cloud Act question remains, and model selection is largely tied to the Azure offering.
Local and on-premise options
Anyone hosting open models themselves achieves the highest degree of data control: there is no external operator and no Cloud Act exposure. The price for this is your own work. Operation, scaling, tool integration, audit logging and governance must be built and maintained in-house. For teams with a strong platform crew this can be right, but for many companies the ongoing effort is considerable.
AIgent
AIgent combines the data control of an on-premise solution with the usability of a finished product. Data resides either in Switzerland or on your own infrastructure, up to air-gapped operation, without any tie to the US Cloud Act. The model is chosen per agent and every step is logged. AIgent Cloud offers Standard/Plus seats with an included usage allowance. AIgent On-Premise has a fixed organisation licence; implementation and infrastructure are priced separately. Contact us to discuss pricing and usage. The technical foundations are described on the page about sovereignty.
The difference lies less in a single feature than in the interplay: data control, agent logic, model choice and audit mesh together rather than being assembled from several separate tools. For companies that want to take responsibility for AI and not just try it out, this very interplay is the decisive point.
A comparison is a snapshot
The market moves fast. Providers add data residency options, extend agentic features and adjust prices. Treat a comparison, therefore, as a snapshot and not as a final verdict. What does not change so quickly are the structural questions: who controls the infrastructure, who is legally liable, and how free you remain in your choice of model. Align your decision with these lasting criteria, not with the feature of the month.
How to make the right choice
There is no universally best platform, only the best one for your requirements. If it is mainly about personal productivity in the Microsoft world, Copilot may be the obvious fit. If you need a strong chat assistant, ChatGPT Enterprise is a serious option. If you have an experienced platform team and maximum control goals, a pure on-premise solution can be right.
Also factor in total cost, not just the list price. Check seat types, included usage and the terms for additional usage. On-premise has a fixed organisation licence plus separately priced implementation, infrastructure and model operation. Calculate over several years and include the internal effort for governance and audit from the start.
If, however, you want to automate tasks, match the model to data sensitivity per use case, and prove every step at the same time, without building your own platform team, a sovereign agent platform is the obvious answer.
Which tasks are worth tackling first in your industry is shown in our overview of use cases. That turns the comparison into a concrete decision.