Somewhere in your company right now, someone is pasting a client contract into ChatGPT to get a fast summary before a call. They are not trying to cause a problem. They are trying to finish a task as efficiently as possible.
Banning ChatGPT at work rarely stops anyone from using it. It just means the company loses visibility into what is being shared with it, and by whom. The fix is building a sanctioned AI chat that is just as fast to use, but is actually allowed to touch company and customer data. There are five real ways to do this: Amazon Bedrock, Google Vertex AI, Microsoft Azure OpenAI Service, Langdock, or Amazee AI. The three hyperscalers, Bedrock, Vertex AI, and Azure OpenAI, can all be made compliant with rules like GDPR and HIPAA, but a company has to do the work of setting them up correctly and keeping them that way. Langdock and Amazee AI are smaller, European-built specialists that treat safe, compliant behavior as the default rather than a setting to configure.
Which of the five fits best depends less on which tool is objectively “best” and more on what a company already uses, and how much extra effort it can realistically put into getting the details right.
Five Ways to Build a Compliant AI Chat
All five platforms let a company run a private, business-grade AI assistant instead of a consumer chatbot with no real legal protections behind it. Here is what each one actually is, and where it tends to help or hurt.
Amazon Bedrock
Amazon’s shared entry point to several AI models through your existing AWS account, with one contract covering all of them.
Bedrock lets companies use several different AI models, including Claude, Llama, and Amazon’s own Titan/Nova models, through their existing AWS account. Its biggest strength is convenience: one agreement with AWS covers every model a company uses through it, instead of separate deals with each AI provider. It only recently became a genuine option for handling sensitive health data, gaining the necessary clearance in February 2026, so it is newer to that role than some companies assume. By default, it does not keep a copy of what is typed in or the answers that come back. The catch is that “allowed to use for sensitive data” is not the same as “automatically safe.” A company still needs someone who understands the settings well enough to keep data in the right place and make sure nothing is quietly misconfigured. Bedrock suits companies that already run on AWS and have some internal technical support to lean on.
Google Vertex AI (Gemini Enterprise Agent Platform)
Access to Google’s Gemini and other AI models through Google Cloud, with a wide choice of European locations for storing data.
Vertex AI gives companies access to Gemini and other models through Google Cloud. Its biggest advantage is choice: it offers a wide range of European locations for storing and processing data, which matters for companies with strict European data rules to satisfy. The drawback is that this flexibility makes it easier to get something wrong. Settings that control where data goes are decided in many different places across the platform, and a single overlooked setting can send information somewhere it should not go, without any obvious warning. Vertex AI can absolutely be run in a fully compliant way. It just asks a lot of an internal team to keep every setting consistent, which makes it a better fit for companies with real in-house cloud expertise rather than a small, generalist IT team.
Microsoft Azure OpenAI Service
The same models behind ChatGPT, delivered through a Microsoft business contract instead of the public app.
Azure OpenAI Service gives companies access to the same underlying models that power ChatGPT, but delivered through a Microsoft business account rather than the public ChatGPT website. For companies already running on Microsoft 365 and Azure, this is often the path of least resistance: the contracts, sign-in systems, and IT relationships already exist. Microsoft’s standard enterprise agreement includes the legal protections needed to handle sensitive health data, and by default customer conversations are not used to further train the underlying models. The catch is that this legal protection existing does not mean the setup is automatically safe: a company still needs someone who understands the settings well enough to deploy it in the right region and keep access properly restricted. It is a strong fit for companies with an existing Microsoft-centered IT setup and at least some internal technical support.
Langdock
A Berlin-based AI platform built to give companies simple, ready-made compliant access to leading AI models.
Langdock gives companies a ready-made, compliant AI chat platform that connects to several leading AI models without requiring any cloud infrastructure work on the company’s own side. It does not build its own AI models. Instead, it gives a company one interface that connects to several leading ones, including GPT, Claude, and Mistral, while keeping the platform and most of the underlying models hosted inside the EU. It does not use company data to train any model, and it holds independent security certifications including ISO 27001 and SOC 2 Type II. It has grown quickly and now serves well over 10’000 companies. The trade-off is cost: Langdock is priced for professional, company-wide use, which can be a stretch for a very small team.
Amazee AI
A Swiss-founded AI platform built to give companies compliant, privacy-first AI access without an in-house compliance team.
Amazee AI is a Swiss-founded platform built for companies that would rather not manage compliance details themselves. A company chooses where its data is handled once, at setup, from options including Switzerland, Germany, the wider EU, the UK, the US, or Australia. It does not keep a record of prompts or answers by default, and it holds recognized independent security certifications, including ISO 27001 and SOC 2 Type II. The honest trade-off is size: Amazee AI is a newer, smaller company, with less of a long-term track record and fewer resources behind it if something goes wrong. It tends to suit companies for whom Swiss-specific data handling is a hard requirement, not just a general preference for “somewhere in Europe.”
Our Conclusion on What to Choose
None of these five is the right answer for every company. The right one depends on what a company already runs on, how much it wants to manage itself versus have handled for it, and how specific its data residency needs actually are.
If a company already runs its systems on AWS, Bedrock is very likely the sensible starting point. The existing contracts, technical relationships, and billing are already in place, and adding Bedrock is a smaller step than starting fresh elsewhere. The same logic applies to a company already built around Google Cloud, where Vertex AI is the natural extension, or a company already centered on Microsoft 365 and Azure, where Azure OpenAI Service fits the same way. In each case, the provider a company already trusts with its infrastructure is usually the path of least resistance, provided there is a technical team capable of keeping the settings right over time.
For companies that would rather not build on top of a hyperscaler at all, the choice comes down to Langdock or Amazee AI, and the difference is mostly about scale and geography rather than capability. Langdock is the better fit for a larger or fast-growing company that wants an established platform with a genuine track record and flexibility across many AI models. Amazee AI is the better fit for a smaller company, or one where handling data specifically inside Switzerland is a hard requirement rather than a general preference for staying in Europe.
Your Next Steps for Building a Compliant AI Chat
The employees already using ChatGPT for work are not going to stop because a new policy says so. The only real fix is giving them a sanctioned alternative fast enough that the unsanctioned one stops being the easier option. That means choosing one of these five platforms based on what fits the company today, not the one with the most features on paper.
Our team can review how AI is currently being used across your company, clarify what your industry’s data protection rules actually require, and help you choose and set up whichever of these five platforms fits best. Get in touch to start with a compliance readiness assessment.
