What Is Langdock? The Berlin AI Platform Explained

What is Langdock? Langdock – written "Langdock AI" in some sources, same service – is an AI platform from Berlin that gives your whole team one centrally managed access point to AI models from several providers in a single interface: GDPR-compliant, ISO 27001-certified, hosted in the EU, with its own AI agents.

According to Salesforce's 2026 AI index for German SMEs (KI-Index Mittelstand), 51.2% of small and mid-sized businesses in Germany are already using or testing AI. In most of them the open question is no longer whether to use AI, but how to keep it under control. This article explains who Langdock is built for, how pricing works, which alternatives exist, and when it actually pays off.

What is Langdock?

Behind the platform is Langdock GmbH in Berlin – you'll find it at langdock.com. What you get is controlled, centrally managed access: one company account for the whole team instead of a private ChatGPT account per employee.

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The difference sounds small but is decisive: with private accounts, nobody in the company has any overview of who is feeding which data into which AI model. With Langdock, everything runs through a central company account – with one place where responsibility sits. For a business, that's the difference between controlled tool use and a blind spot in your IT.

There's a second point that weighs more in daily use than it sounds: Langdock isn't tied to a single AI model. Your team works with models from several providers in one interface – and switches when another model fits a task better, without a second account.

Who is Langdock built for?

One team, one access point: every desk works through the same managed platform instead of private AI accounts.

Langdock is aimed at companies that don't just want to try AI but build it into everyday work – with multiple people, multiple departments, real data. Langdock names Merck and Personio among its references. That tells you the platform is built for company-grade requirements, not just individual users.

For SMEs, that means something concrete: if your team currently runs on a patchwork of private AI accounts – one colleague has ChatGPT Plus, another uses nothing at all – Langdock creates one unified, controlled access point for everyone.

Data protection and security: the three points that matter

For an AI tool in business use, three things are non-negotiable. Langdock meets all three:

• GDPR-compliant. Your data is processed under the European General Data Protection Regulation. A data processing agreement (DPA) – the written contract that defines who processes which data on whose behalf – comes as standard.
• ISO 27001-certified. This certification confirms an independently audited information security management system – a checked standard, not a marketing claim.
• EU hosting. Your data sits on servers inside the EU. That isn't the same as hosting in Germany – but for most SMEs, EU hosting is exactly what matters: the data stays inside the European legal space. For your specific case, read the DPA – for example, which model providers are involved and where they process data.

For a company feeding sensitive customer or business data into an AI, these are the three questions to settle before looking at any other feature.

In practice: who is allowed in, and what each department may use, is set centrally – which administration options exist in detail is documented by Langdock itself. How to set those permissions up cleanly at the start – and which mistakes make rollouts fail – is covered step by step in Rolling out Langdock: the practical guide.

This is our practical assessment, not legal advice – for a binding evaluation of your use case, talk to your data protection officer or a lawyer.

What can Langdock's AI agents do?

Langdock is more than a chat window. Through the platform, you can build your own AI agents – without code: fixed helpers that take over a recurring task instead of being prompted from scratch every time. Pre-sorting email, drafting proposals from a briefing, summarizing research, answering standard inquiries.

The advantage over a stand-alone solution: the agents run in the same environment as the rest of your team – same data protection level, same control. What such agents realistically take over in a business is covered in AI agents for SMEs.

Langdock or ChatGPT: is ChatGPT enough for the team?

A fair question, and the honest answer: for a one-person business or pure experimentation, a single ChatGPT account is often perfectly fine.

Langdock starts to pay off once several people work together and company responsibility enters the picture: when you need to know who is entering which data. When different departments need different permissions. When you want to build shared agents the whole team uses, instead of everyone maintaining their own chat history. When data protection credentials – GDPR, ISO 27001, EU hosting – matter to you or your customers. In short: the moment "I'm trying out AI" turns into "we work with AI", a controlled platform usually beats a collection of private accounts.

What are the alternatives to Langdock?

Anyone looking for a Langdock alternative usually compares three other routes: the team plans of the model providers themselves, the AI assistant inside the office suite they already use, or simply letting private accounts continue. Here's how the four options compare (as of September 2026; statements about ChatGPT and Copilot are based on the vendors' public information):

Criterion	Langdock	ChatGPT Team / Enterprise	Microsoft 365 Copilot	Private individual accounts
Vendor and location	Berlin, EU hosting	OpenAI, USA – EU data storage only in certain plans	Microsoft, USA – data within your Microsoft 365 contract	Various
Model choice	Models from several providers in one interface	OpenAI models only	Predominantly OpenAI models, integrated in Office	One per account
Central administration	Yes, central company account	Yes	Yes, via Microsoft administration	No
Custom AI agents for the team	Yes, no code, shareable across the team	Yes ("GPTs"), shareable in the workspace	Yes (Copilot agents), strongly tied to the Microsoft environment	No, or private only
Best fit for	Teams that want data protection credentials and model freedom	Teams already fully committed to OpenAI	Businesses living deep inside Microsoft 365	Individuals, experimentation
Data protection – what you must check	GDPR-compliant, ISO 27001, DPA as standard	DPA and storage location in the chosen plan	Within your existing Microsoft 365 contract	No central proof possible

Our assessment: Langdock, ChatGPT Team and Microsoft 365 Copilot are all three serious platforms – private individual accounts, by contrast, aren't a solution but the problem the other three fix. For a business that already lives entirely in Microsoft 365, Copilot can be the shorter route. Langdock wins clearly in two situations: when data protection credentials with an EU base matter to you or your customers, and when you don't want to tie your team to a single AI model. Plans and storage locations change – check them for your case.

When Langdock is not the right answer

Langdock is strong – but it's not the answer to every problem. If your real bottleneck is a process, not access to knowledge, an automation with Make.com or n8n is often the faster lever: it connects systems without anyone actively operating an AI. If what you're missing is basic structure rather than automation, a project management solution like SmartSuite is the better first step. And if no existing tool fits, you need custom development. A platform like Langdock doesn't replace process design – it makes AI accessible and controllable for your team. What you build with it is still work.

What does Langdock cost?

The licence comes from Langdock. The current pricing model and tiers are on Langdock's own site – they change and depend on team size and feature scope, and we'd rather not print numbers here that could be outdated tomorrow.

What we contribute on top – rollout, team training, custom agent development, connecting your existing systems – runs separately: as a fixed-price kick-off sprint (SCALE², three weeks) and then as ongoing support over several months, billed monthly and agreed up front. Because an AI platform is only truly rolled out once the team actually uses it – measured by weekly active users and by how much of that usage runs through agents rather than plain chat. Details are on our Langdock page.

What getting started looks like in practice

A Langdock rollout starts with three blocks of work – and then doesn't stop. First: setup and permissions – who gets access, which department may do what, how data is handled internally. Second: hands-on training that doesn't start from abstract examples but from the tasks your team already handles every day – emails, proposals, reports. Third: optional, but often the real lever – developing the first custom agents for the tasks that cost your business the most hours.

How fast a team becomes productive depends on preparation and on the use case you pick – that can't be promised in general terms. We plan setup, training and the first custom agents as a SCALE² kick-off sprint: three weeks, five phases from analysis to go-live, three weeks of support afterwards included. Go-live is the start, not the finish line: after that we stay on board for several months with workshops and fixed check-ins until usage sticks in daily work.

Our advice for starting out: begin with one department and one concrete use case instead of converting the whole company at once. If the benefit shows – measured in hours actually won back – you scale from there. If it doesn't, you found out at manageable cost instead of having sunk money into a company-wide rollout that never pays off.

How Langdock fits into existing workflows

An AI platform only delivers real value once it's not sitting isolated next to your daily business but connected to the systems where your data lives – CRM, inbox, document storage. An agent that's supposed to answer an inquiry but has no access to the customer history in your CRM can only ever do half the job.

That's why, for us, Langdock is rarely a solo act: the platform covers controlled access to AI; connecting your existing systems comes as the second step. The same principle applies here as with everything we build: your systems stay in place, and Langdock plugs into them. How we handle both steps is described on our Langdock page.

Our experience with Langdock

We don't recommend Langdock from the sidelines: we use the platform ourselves, every day. All of our 40-plus own AI agents run in Langdock – alongside further agents and AI workflows elsewhere in the business. We try things out on our own business before we suggest them – if a feature doesn't convince us internally, it doesn't make it into a client recommendation. Search for Langdock reviews and you'll find plenty of feature lists and very little everyday reality. So here's ours, unvarnished:

The value sits in shared agents, not in the chat. Chat is the entry point, but that isn't where Langdock started to pay off for us: an agent that's been built properly once is available to the whole team. Nobody types the same context for the twentieth time, nobody starts from zero – the knowledge lives in the agent, not in one person's chat history.

Our concrete flagship: the bookkeeping agent. It has access to SevDesk, our bank account and our email inbox. As its knowledge base we've given it bookkeeping material, our chart of accounts and the relevant German tax laws – income tax, VAT, trade tax. No model is trained on any of that; Langdock doesn't use customer data for training. Questions like "Is there a receipt missing for this payment?" it answers straight from the real data, instead of someone clicking and searching. How our bookkeeping runs around 90% automated overall is the full story in Automate your bookkeeping.

What surprised us: an agent isn't finished once it's set up. The first version rarely lands. An agent needs sharpening, maintained knowledge sources and a human who feels responsible – otherwise quality quietly drifts. If you expect to configure an agent once and never touch it again, you'll be disappointed. For us, revising agents is part of the routine – and that's exactly why they work.

Bottom line: we'd roll out Langdock again – and we guide rollouts for clients. But as a tool that takes work to save work. Not as a miracle machine.

Frequently Asked Questions

Is Langdock AI something different from Langdock?

No. "Langdock AI" and "Langdock" refer to the same platform from Langdock GmbH in Berlin. The longer spelling mostly shows up in international sources and in Google results. If you come across the name in that form in a tender, a quote, or on a comparison site, it isn't a different product or a different company – you can check the claims directly against this article.

Is Langdock a fit for small companies?

Yes – if several people work together and control over company data matters. The benefit depends less on company size than on whether your team works with AI together: as soon as permissions, chat histories, and shared agents play a role, a managed access point makes sense. If, on the other hand, one person works with AI alone, a simple individual account is usually enough.

Do we need our own IT department to roll out Langdock?

No. Langdock is operated as a cloud service, hosted in the EU – there's nothing for you to install. Setup and permission management can be handled externally, and your team usually needs nothing more than hands-on training to get productive. What you do need internally isn't an IT department but one person who owns the platform: creating users, maintaining permissions, being the point of contact for questions.

Does Langdock use our data to train AI models?

No. Langdock states that customer data is used to process your requests, not to train AI models. On top of that, Langdock is ISO 27001-certified and hosts in the EU. Which model providers are involved in the background, and where they process your data, is something Langdock documents in its data processing agreement (DPA) – worth reading before real customer data goes into the platform. This is our practical assessment, not legal advice.

Which AI models can I use in Langdock?

Langdock bundles models from several major providers in one interface, and access is managed centrally. Which models are available at any given time changes with every new model generation – the current list is documented by Langdock itself, worth a look before you commit. For you as a business, the relevant point isn't the model of the month but the freedom to switch when a better one comes along, without opening a second account anywhere.

The next step

If you want to know whether Langdock is the right lever for your team – or whether an automation or custom software gets you there faster – the Time Potential Analysis is the simplest first step: 45 minutes, free, no sales pitch. More on rollout, training and agent development on our Langdock page. Book your Time Potential Analysis →