01 — Approach
What Langdock is and who it fits
Langdock is an AI platform from Germany that gives your team access to ChatGPT, Claude, Gemini and dozens of other models under one interface. GDPR-compliant, with EU hosting, a data processing agreement and central permission management. Instead of every employee working with a private ChatGPT account while nobody knows where the data flows, there is one place with clear rules.
It fits best for companies from around twenty employees upwards that want to bring AI broadly into the team without building their own infrastructure. We have worked with these models since the first GPT-3 APIs, and before that we spent twenty years introducing digital projects. That combination helps more with Langdock than any feature knowledge, because a rollout is ultimately a change project with people, not a software setup. If you are wondering whether all this is legally sound: we cover the compliance side in depth under compliant AI, and Langdock is regularly our answer there when the question is about the pragmatic route.
02 — Current
What's changing at Langdock right now
Langdock keeps evolving fast. In June 2026, Claude Sonnet 5 arrived on the platform, and in July the GPT-5.6 family from OpenAI followed in three variants, all hosted in the EU. For you that means: you get new frontier models usually within days of release, without renegotiating contracts or re-reviewing data flows.
Exciting for daily work is the new Excel integration, which makes knowledge bases, skills and workflows usable directly inside spreadsheets. And with the Agents feature, currently in beta, the first agentic workflows are growing into the platform. We watch this closely and only activate new functions for our clients once they run stably and fit the permission concept.
Our take: the model race is Langdock's problem, not yours. What matters is that your assistants and prompts are built so that a model switch makes them better instead of breaking them. That is exactly how we build them.
03 — Practice
Rollout: from the license to daily operations
With us, a Langdock rollout is a project with clear stages. First the foundation: workspace configuration, SSO integration, roles and permissions, model selection and the rules for which data may be uploaded. Then a pilot with a department that has real demand, usually two to four weeks. Only once the pilot holds up do we roll out to the whole team. This sequence sounds slow, but it is the fastest path to real usage, because the pilot group becomes your internal advocates.
Want to know what such a rollout would look like at your company? In a no-strings first call we will sketch the stages, the effort and a realistic timeline for your team size.
04 — Practice
Knowledge bases that actually deliver answers
The biggest lever in Langdock is connecting your knowledge: manuals, process documentation, product data, Confluence, SharePoint, Google Drive. Sounds like one click, but it isn't. If you simply upload everything, you get answers based on outdated versions and drafts. We curate the sources, clarify who is responsible for keeping them current and test with real questions from daily work before a knowledge base goes live. The result: answers the team trusts.
05 — Practice
Custom assistants for departments
The standard chat is the beginning, but the impact comes from specialized assistants. A proposal assistant for sales that knows your pricing logic and text modules. An HR assistant that writes job ads in the company's voice. A support assistant that sits on top of the knowledge base and delivers draft replies. We build these assistants together with the departments that will use them, test them against real cases and document what they can and cannot do.
06 — Practice
Onboarding and adoption tracking
The uncomfortable truth about AI platforms: after the launch enthusiasm, usage drops if nobody steers. So every rollout includes an onboarding that builds on our AI training, with real tasks instead of slides. After that we look at the usage data monthly: who actively works with the platform, which assistants get used, where things get stuck. Those numbers drive refresher trainings, new assistants, or the decision to switch off an unused one.
An AI platform is only truly adopted when it gets opened on a Tuesday afternoon for no particular reason.
07 — Honest
Where Langdock ends and code begins
Langdock is strong when people work with AI: chatting, researching, producing texts and analyses. It is not the right tool when AI is supposed to run without people. As soon as you want to process thousands of documents automatically, build AI firmly into your software or trigger multi-step processes without a click, a direct API integration with its own setup is the cleaner solution. What we build then is described on our page about AI implementation. Often the answer is both: Langdock for breadth across the team, an API integration for the one high-volume process. How that fits together into one strategy is shown in the overview of our AI services.
Langdock already in-house or still on the list?
Tell us briefly how big your team is and what you plan to do with AI. We will tell you honestly whether Langdock fits, what a rollout takes and where you should start. First call free of obligation, 30 minutes.