amaiko vs Langdock: Teams-Native, Proactive AI vs the Model-Agnostic Workspace (2026)

What Langdock does genuinely well

Let’s be clear up front: of all the platforms we compare on this site, Langdock deserves the most respect. This is not a feature-stuffed US import with a German landing page — it is a Berlin-built enterprise AI platform with reference customers most vendors would kill for. Pretending otherwise would be dishonest, and you would notice.

Real enterprise traction. More than 7,000 companies use Langdock, including Merck with 33,000 monthly active users, Der Spiegel and Dr. Wolff. Names like that are not won with marketing — they are won with a product that survives procurement, works councils and security review.

Genuine model agnosticism. Langdock gives your team access to more than 40 models — GPT-5.x, Claude Opus and Sonnet, Gemini and more — behind one interface, plus an EU-hosted API proxy. No vendor lock-in, no waiting on a single provider’s roadmap. That is a real architectural commitment, not a checkbox.

Mature workflow automation. The drag-and-drop workflow builder, scaling from 2,500 to 100,000 runs per month depending on package, is more mature than most competitors offer at this price point. Combine that with SSO, SCIM, SAML, admin governance, usage analytics — and on-premise deployment at the enterprise tier — and Langdock covers the enterprise checklist properly.

And it is German-hosted and GDPR-compliant, which we will come back to below — because for once, that is not where the difference lies.

So why does this page exist? Because being an excellent AI workspace and being the right AI architecture for a Teams-centric company are two different things.

Three structural differences

The amaiko vs Langdock question comes down to three architectural decisions — not feature gaps the next release fixes, but choices about what kind of product each one is.

Langdock waits. amaiko doesn’t.

Langdock is a chat-and-agent layer: every interaction starts with a person opening Langdock and typing. The agents are capable, but they are reactive — there is no proactive monitoring, no push intelligence, no system that acts on your behalf before you ask. amaiko inverts that. It watches your company’s signals and moves first: your morning briefing is ready before you open the laptop, your inbox is triaged before you read it, meeting follow-ups appear without anyone asking. A reactive platform saves you minutes when you remember to use it; a proactive one saves the minutes you didn’t know you were losing.

A separate app is a context switch

Langdock has no Teams-native presence. For a company that runs on Microsoft 365 — and that is the company we build for — every AI interaction means leaving Teams, opening Langdock, re-establishing what you were doing, and copying the result back. It is a small tax paid dozens of times a day, and it is exactly the kind of tax that erodes adoption in practice. amaiko lives inside Teams: the AI is in the chat where the work already happens — same window, same thread, zero switching. See how that works in practice.

Configured agents are not a memory

Langdock’s custom agents are genuinely useful: task-specific, shareable across the team. But each agent knows what someone explicitly configured it to know — the platform does not accumulate knowledge about your company on its own. amaiko builds a persistent, self-learning corporate memory that grows with every interaction: decisions, context, who knows what, why things were done the way they were. When an employee leaves, their context stays. The measurable effect for amaiko teams: 35% less time spent searching and onboarding up to 57% faster, because new hires inherit a memory instead of an empty workspace.

The GDPR card doesn’t decide this one

On most pages in this section, data residency is a differentiator. Here it isn’t, and we would rather tell you that than manufacture one. Langdock hosts in German and EU data centers, is GDPR-compliant, has a SOC 2 audit in progress, and offers on-premise deployment at the enterprise tier. That is a clean European posture, full stop. amaiko hosts 100% in Germany and is certified against ISO 42001, the management standard for AI systems — a certification layer on top of the same German-hosting foundation, not a different foundation. If GDPR compliance is your only criterion, both vendors pass. Make the decision on the three differences above, not on a compliance gap that does not exist.

The pricing reality

Langdock’s per-seat pricing starts reasonable and stacks fast. The Business plan is €25 per user per month; Business Max, with five times the usage allowance, is €99 per user per month. Workflow automation includes 2,500 runs per month with Chat & Agents — scaling to 100,000 runs is a €539 per month add-on. The API product passes model pricing through with a 10% token markup. Run the numbers for a 100-person organization on the standard plan: €2,500 per month before workflow costs, and the bill climbs steeply once power users move to Business Max. There is a 7-day free trial; enterprise pricing — 1,000+ users, dedicated deployment — is custom.

amaiko starts at €19.92 per user per month, billed annually — with proactive intelligence, the multi-agent network and corporate memory included, not stacked on top.

Who should choose which

Honest segmentation — and Langdock earns a real “choose them” list.

Choose Langdock if you want a model-agnostic AI workspace where teams hand-pick from 40+ models, your priority is drag-and-drop workflow automation today, your company does not live in Microsoft Teams, or you are a 1,000+ seat enterprise that needs on-premise deployment. Within that brief, it is one of the best options built in Europe.

Choose amaiko if your company runs on Microsoft Teams and you want AI that is native there instead of another app to open; if you want intelligence that acts before you ask; and if you want a corporate memory that builds itself instead of agents you have to configure. Rollout is a single Teams chat — no workspace migration, no training program.

Running both is technically frictionless — Langdock is a separate app, amaiko lives in Teams — but they occupy the same budget line, so in practice most companies pick one based on where their work actually happens. If it happens in Teams, that answers the question.

If you are surveying the wider field, our roundup of Langdock alternatives covers the other contenders. And if you would rather see proactive AI than read about it: book a demo — it takes one Teams chat to show you.