GDPR-compliant AI platforms for enterprises compared 2026

Status May 2026. Features and terms change. We recommend checking the latest data with each vendor directly.

Generative AI has arrived in European enterprises in 2026, but in many organisations there is still a gap between use and clean compliance. Employees reach for ChatGPT on personal accounts, paste confidential data into public tools, and nobody can demonstrate where exactly what content has been processed. With the substantive provisions of the EU AI Act taking effect on 2 August 2026, the everyday practice turns into a regulatory issue.

The good news for the DACH region: the market for GDPR-compliant AI platforms has matured. Between Berlin, Hamburg, Rosenheim, Aachen and Heidelberg vendors have emerged that explicitly target the mid-market and enterprise segment while competing with US cloud giants such as OpenAI or Microsoft. Anyone shopping for enterprise AI today can choose between multi-tenant SaaS, dedicated SaaS tiers, self-hosting in their own cloud, and full on-premise setups.

This article compares 19 AI platforms for enterprises in the DACH region – including basebox.ai. At its core sits a detailed comparison table, followed by deep-dive profiles of the nine most relevant vendors. We then look at which hosting model fits which type of organisation, how the cost structure develops qualitatively across three realistic scenarios (50, 200, 1,000 users) and what the EU AI Act concretely requires. Short answer: for most mid-sized and large organisations with a data-sovereignty requirement, CompanyGPT by innFactory AI Consulting is the clear winner – no per-user licence, STACKIT as standard and §203 StGB architecture, and a cost model that is structurally more economical than per-user SaaS platforms as headcount grows.

What a GDPR-compliant AI platform must deliver

An AI platform that wants to sustain in the enterprise context must address four requirements at the same time: lawful data processing, technical data sovereignty, regulatory alignment with the EU AI Act and verifiable control over model choice and data flows.

GDPR compliance starts at the hosting layer. The personal and business data that is processed must not leave the EU in an uncontrolled way. Vendors with a production environment in the EU (Azure West Europe, AWS Frankfurt, Gemini Enterprise Agent Platform Frankfurt, STACKIT Berlin) and a clean data processing agreement satisfy this requirement. The US CLOUD Act remains a residual risk where the parent company is US-based even if the data centre is in Frankfurt. Anyone who wants to rule out that risk has no way around a European sovereign cloud.

EU AI Act compliance is the second layer. From August 2026 companies must classify their AI systems, meet transparency duties and demonstrate sufficient AI competency. Platforms that provide auditability, logging, model documentation and training material make this proof significantly easier. External advice from a specialist IT lawyer is essentially unavoidable in most mid-sized organisations.

Zero-data-retention is the third requirement. With US providers such as OpenAI, Anthropic and Google it is regularly secured contractually through the enterprise or cloud offerings of the hyperscalers, with classical B2C services it is not. A platform should be transparent about which data goes to which model provider and whether it is excluded from training.

Data sovereignty is the fourth dimension. It ranges from multi-tenant SaaS (shared infrastructure, fast start, low control) through dedicated SaaS (your own instance at the vendor) and self-hosting in your own cloud (full control, moderate complexity) to on-premise on your own servers (maximum isolation, highest operational effort). The right choice depends on the protection level of the data being processed, the available IT skill set and the desired time-to-value.

The big comparison table: 19 AI platforms in the DACH region

The following table compares 19 vendors along the most relevant criteria – including basebox.ai. It scrolls horizontally.

Three patterns stand out. First, the per-user pricing model dominates the DACH market. Second, several vendors add additional cost factors such as token quotas or separately bookable modules on top, so effective annual cost can rise significantly at 200 or 1,000 users. Third, the combination of self-hosting from the first user, no per-user surcharge and integrated specialised-lawyer compliance is rare – CompanyGPT by innFactory AI Consulting is currently the only DACH platform that satisfies all three at once, with a predictable fixed-price/maintenance model regardless of headcount (terms on the product page).

Deep-dive on the nine most relevant vendors

CompanyGPT (innFactory AI Consulting)

CompanyGPT is the AI platform of innFactory AI Consulting GmbH from Rosenheim. The technical base is a hardened, production-grade variant of LibreChat. The platform is installed inside the customer’s cloud, optionally on STACKIT (Berlin, sovereign cloud), Azure West Europe, AWS Frankfurt or Google Cloud Frankfurt. Data permanently stays inside the customer environment.

The pricing model is structurally different from the market: no per-user licence cost, but a predictable fixed-price/maintenance model independent of headcount (terms on the product page). Token cost of the model providers (Azure OpenAI, AWS Bedrock, Gemini Enterprise Agent Platform) is passed through at list price.

Functionally CompanyGPT covers the essential enterprise needs: model choice across GPT, Claude, Gemini, Llama, Mistral and Perplexity, the add-ons companyFILES (Office file editing), companyRAG (knowledge base, SharePoint integration with permission mirroring), companyTRANSLATE (enterprise translator) and companyDASHBOARD (reporting). MCP server support and n8n workflows are integrated natively. Compliance advisory including a specialist IT lawyer (AI guideline, AI officer training) is part of the setup fee.

Reference customers include Rohrdorfer Group, Schön Klinik, ift Rosenheim and Duschl Ingenieure.

Strengths: No per-user licence, own cloud from day one, native MCP and n8n integration, integrated compliance advisory and training, transparent token cost without markup.

Limitations: No self-service signup for very small companies, no native mobile app (responsive web), higher setup effort than a pure SaaS, operated on the cloud infrastructure of the hyperscalers (Azure, AWS, GCP) or STACKIT.

Target audience: Mid-sized companies and corporations from 30 to 50 users that need full data sovereignty, predictable cost and integrated compliance.

DeutschlandGPT (Titanom Technologies)

DeutschlandGPT is a SaaS product by Titanom Technologies GmbH from Germering near Munich. The platform uses a multi-tenant architecture hosted in Germany. The German hosting makes DeutschlandGPT popular in regulated sectors.

Pricing is classical SaaS: a per-user licence in the Business plan, free entry via a complimentary plan; the vendor states the current terms. The vendor reports more than 300 organisations (according to the provider) using the platform, including several public agencies and mid-sized companies.

Strengths: Hosting in Germany, quick onboarding, free plan, clearly German vendor environment.

Limitations: In the standard SaaS tier multi-tenant; self-hosting and SharePoint integration are not listed in the public pricing overview (Titanom offers both separately in its project business); MCP support is not stated on the product page. Per-user pricing scales linearly with headcount.

Target audience: Public authorities, municipalities and mid-sized companies that put hosting in Germany first and can live with multi-tenant SaaS.

Why CompanyGPT is the better choice: No per-user licence instead of a per-user model – per-user models scale linearly with headcount, whereas CompanyGPT’s maintenance-based model stays independent of it, and the cost advantage grows with company size. On top of that: self-hosting in the customer’s own cloud (STACKIT, Azure, AWS, GCP) from the first user instead of multi-tenant standard, native MCP and n8n integration, and specialised AI lawyer compliance plus training included in the setup fee.

Langdock

Langdock is one of the most visible AI adoption platforms from Berlin. It names prominent reference customers on its own website (Merck, BASF, Der Spiegel, UNICEF). Langdock is hosted in the EU (Microsoft Azure) and offers flexible deployment options (Managed Cloud, Single-Tenant, bring-your-own-cloud, on-premise from larger seat tiers).

The pricing model is a SaaS model; the current terms are listed by Langdock on its own website.

Strengths: Access to all leading models, strong enterprise references, flexible deployment options, EU hosting, fast UX.

Target audience: Organisations focused on a fast SaaS rollout. A detailed comparison is available in CompanyGPT vs. Langdock.

Difference to CompanyGPT: CompanyGPT follows a different model – no per-user licence model, deployment in the customer’s own cloud from the first user, plus native MCP and n8n integration and integrated compliance advisory with a specialist lawyer. Which approach is more economical depends on headcount and usage intensity and should be calculated against each vendor’s current terms.

Omnifact

Omnifact is a German vendor that positions a Privacy Filter as its main differentiator. Incoming prompts are scanned for personal data and automatically masked before being sent to model providers.

Pricing is per user (Starter/Pro/Enterprise tiers). The Pro tier includes a limited monthly AI credit for premium models; base models remain usable beyond that. Current terms are stated by the provider. An on-premise option is available for enterprise customers (plus private-cloud/air-gapped).

Strengths: Automatic data masking via Privacy Filter, on-premise option in Enterprise tier, clearly German vendor profile.

Limitations: Limited monthly AI credit for premium models in the Pro tier, smaller functional ecosystem than multi-model platforms, MCP and workflow support limited.

Target audience: Companies with particularly high protection requirements for personal data, who set a visible technical filter as a selection criterion.

Why CompanyGPT is the better choice: No per-user licence and no capped AI credit – per-user models scale linearly with headcount, whereas CompanyGPT’s maintenance-based model stays independent of it, and the cost advantage grows with company size. Token cost passes through 1:1 at the hyperscaler’s list price (Azure, AWS, GCP, STACKIT), MCP and n8n workflows are native instead of “limited”, and specialised AI lawyer compliance plus training are part of the setup fee instead of an optional add-on.

basebox (basebox.ai)

basebox is a self-hosted AI platform built by basebox GmbH from Utting am Ammersee in Germany, positioning itself as a “Secure AI Stack” and “Sovereign AI Stack” for regulated industries – healthcare, finance, public sector and manufacturing. Technically the platform runs on Kubernetes and Helm charts and offers an app store with curated AI apps (chat, translation, “ask your PDF/Excel/Word”), a no-code app builder, knowledge management and SSO via OIDC, AD and LDAP. Deployment: cloud (managed), on-premise (Kubernetes/Helm, Docker Compose unofficial) or hybrid. A prominent healthcare reference is Deutsches Herzzentrum München.

Pricing is user-based, annual licensing (minimum 1-year term, all features included) with a token component per the provider’s pricing page; concrete tiers and pricing are stated by the provider directly.

Strengths: Healthcare references, app-store model with ready-made apps, no-code app builder, hybrid deployment, clear sovereign-AI brand positioning.

Limitations: User-based annual licensing plus a token component (see provider), no publicly documented STACKIT partnership, no integrated specialised-lawyer compliance, MCP support not declared productive. basebox addresses §203 StGB in its legal terms as a service provider for professional-secrecy holders, via self-hosted operation rather than a documented hyperscaler addendum.

Target audience: Regulated mid-sized companies in healthcare, finance and public administration that prefer a finished product with an app store and an app builder and can absorb user-based annual licensing plus a token component.

Why CompanyGPT is the better choice: No per-user licence and no token component instead of user-based annual licensing as headcount rises – user-based models scale with headcount, whereas CompanyGPT’s maintenance-based fixed-price model stays independent of it, and the cost advantage grows with company size. On top of that: documented STACKIT partnership (Schwarz Digits) with Qwen3-235B as the flagship model, §203 StGB add-on agreement with Microsoft inside the customer’s own Azure subscription, native MCP and n8n integration, SharePoint permission mirroring, and integrated specialised AI lawyer compliance. Full detail comparison: CompanyGPT vs. basebox.

amber (formerly amberSearch)

amber is a vendor from Aachen that originally comes from the enterprise search space and more recently expanded its portfolio with AI assistants and agents. The vendor reports more than 400 companies as customers (according to the provider). The platform combines classical full-text search with semantic search and LLM-driven answer generation.

The platform is offered as both SaaS and on-premise. Standard plans are publicly listed; enterprise terms depend on data volume and number of users.

Strengths: Deep enterprise search experience, large number of production installations, flexible hosting options.

Limitations: Primarily search focused, chat and agent capabilities narrower than pure LLM platforms, less visible workflow automation.

Target audience: Larger mid-sized companies and corporations that want to make central knowledge bases searchable and progressively add AI answers on top.

Why CompanyGPT is the better choice: No per-user licence, self-hosting in your own cloud, native MCP and n8n integration, and integrated AI compliance advisory with a specialised lawyer. Anyone needing enterprise search and LLM answers under one platform with their own cloud and without a per-user surcharge benefits from the maintenance-based model: per-user models scale linearly with headcount, whereas CompanyGPT stays independent of it – companyRAG plus n8n covers the classic amber use case as well.

neuland.ai

neuland.ai positions itself as an AI management and orchestration platform with an “AI First” approach. neuland.ai AG, based in Cologne, was founded in 2023 (co-founded by Karl-Heinz Land) and announced a €3.5M pre-Series-A in early 2026.

The platform bundles pre-built AI apps, workflow building blocks and industry-specific solutions – including Industry Competence Models (ICMs) in the Enterprise tier – under one interface. It follows a multi-LLM strategy (GPT, Claude, etc.). Prices are not publicly listed and are tailored to specific needs.

Strengths: Platform approach with AI apps and workflows, multi-model strategy, industry solutions.

Limitations: No transparent pricing, lower public visibility than DeutschlandGPT or Langdock, MCP and n8n support not documented.

Target audience: Companies that want to use AI not only as a chat tool but as a platform with various business applications. Detailed comparison in CompanyGPT vs. Neuland.ai.

Why CompanyGPT is the better choice: Transparent terms instead of “on request”, no per-user licence, native MCP and n8n support, and specialised AI lawyer compliance in the setup fee. At 200 or 1,000 users CompanyGPT stays structurally on a maintenance-based fixed-price model instead of scaling linearly with headcount – industry-specific solutions are delivered through companyRAG plus n8n templates without licence cost growing with them.

Telekom Business GPT (Deutsche Telekom)

Deutsche Telekom offers Business GPT as a fixed-price package model. The platform sits on OpenAI models in a Microsoft cloud specifically secured for Deutsche Telekom in Europe. Packages are offered as fixed-price packages with a minimum user count (entry from 50 users). Note that some of the most recent officially dated product information dates in part from 2024.

The advantage is a clear contractual framework with a well-known provider: one point of contact, a German invoice, a familiar contract logic. The platform itself is more narrowly scoped than the multi-model solutions from Berlin or Rosenheim.

Strengths: Trusted Deutsche Telekom brand, operated in a Microsoft cloud specifically secured for Deutsche Telekom in Europe, one point of contact for contract and support, fixed-price model for predictable cost.

Limitations: Limited model choice (effectively GPT), no open source, proprietary platform, no self-hosting, no MCP support.

Target audience: Corporations and public-sector buyers that value a known German vendor with a clear contractual framework. Detailed comparison in CompanyGPT vs. Telekom Business GPT.

Why CompanyGPT is the better choice: Free model choice (GPT, Claude, Gemini, Llama, Mistral, Perplexity) instead of only GPT, native MCP and n8n support, no package jump as usage grows, and no per-user licence – the maintenance-based model stays independent of headcount while package and per-user models grow with it. Open-source components and MCP extensions instead of a proprietary platform avoid lock-in to a single hyperscaler.

Microsoft 365 Copilot

Microsoft 365 Copilot is the native AI integration in Office 365. It lives directly inside Word, Excel, PowerPoint, Outlook and Teams and reaches through Microsoft Graph into SharePoint, OneDrive and the mailbox. The underlying models are GPT variants on Azure OpenAI.

Licensing is per user and month, on top of Microsoft 365 prerequisites (E3 or E5); the vendor states the current terms. Microsoft offers several GDPR addenda and the EU Data Boundary. From a legal perspective the US jurisdiction and the CLOUD Act remain a discussion point.

Strengths: Seamless integration into Office 365, very wide adoption in the mid-market, native Office file editing, simple user management via Microsoft Entra ID.

Limitations: US jurisdiction (CLOUD Act), no model choice, no self-hosting, no open source, linear per-user cost, functionality outside M365 limited.

Target audience: Office-365-centric organisations that primarily want to experience AI in Word, Excel, PowerPoint and Outlook and can contractually deal with the US jurisdiction. Copilot complements a GDPR-compliant primary platform but rarely replaces it. A view from outside Copilot is in LibreChat vs. Open WebUI vs. Copilot.

Why CompanyGPT is the better choice: No US jurisdiction and no US CLOUD Act risk, free model choice instead of only Azure OpenAI, native MCP and n8n support, and no per-user licence – per-user models scale linearly with headcount, whereas CompanyGPT’s maintenance-based model stays independent of it, and the cost advantage grows with company size. For pure Office-365 features Copilot remains a sensible add-on; as a GDPR-compliant primary platform CompanyGPT closes the sovereignty and cost gap – including companyFILES for active Office generation inside the customer’s own cloud.

Decision guide: which hosting model fits your company?

The right hosting model depends on four factors: the protection level of the data being processed, the available IT skills, the desired time-to-value and the long-term cost dynamic. In practice four profiles emerge.

Multi-tenant SaaS is the right choice when the company wants to start fast, the data has low to medium protection requirements and the per-user pricing is currently still economical. Platforms such as DeutschlandGPT, Omnifact, Lurus and Logicc belong here. Upside: no setup effort, immediate availability. Downside: less control, linear cost development, no protection from the US CLOUD Act where the parent company is US-based.

Dedicated SaaS solves some of the weaknesses of multi-tenant. The platform runs in a dedicated instance at the vendor with dedicated storage and often better SLAs. Langdock and DeutschlandGPT offer this in higher tiers; the vendors state the details. Upside: better data isolation, easy maintenance. Downside: significantly higher pricing, continued vendor dependency.

Self-hosted in your own cloud is the choice when full data sovereignty is required without operating an own data centre. The platform is installed in the customer’s cloud (STACKIT, Azure, AWS, Google Cloud). CompanyGPT, DSGPT, kamium and partially PhariaAI follow this model. Upside: data never leaves your environment, model choice flexible, cost independent of headcount. Downside: higher initial setup effort than pure SaaS.

On-premise on your own servers is the choice for the strictest protection requirements, for example in banking, healthcare or critical infrastructure. PhariaAI, Omnifact Enterprise and DSGPT offer true on-premise variants; WilmaGPT uses dedicated servers in German data centers. Upside: complete isolation, no cloud provider in the picture. Downside: highest operational effort, GPU investment, scaling more demanding.

A pragmatic recommendation for most DACH mid-sized companies: self-hosting in your own cloud meets the intersection of sovereignty, time-to-value and cost best. On-premise pays off only with special protection requirements, multi-tenant SaaS remains a valid choice for pure pilots with non-critical data.

Cost comparison: how enterprise AI costs develop structurally

List prices say little about total cost. What matters is the cost structure. Three realistic scenarios show how TCO develops qualitatively over a year – concrete terms are best calculated per vendor.

Scenario 1: 50 users, moderate usage. At this size, per-user SaaS platforms incur licence cost that rises with headcount, plus token usage. CompanyGPT works with a one-off setup plus ongoing maintenance, then only the maintenance share. From the second year onwards the maintenance-based model is structurally more economical than a typical per-user model.

Scenario 2: 200 users, intense usage. At 200 users, per-user SaaS platforms scale with headcount, plus token cost and, where applicable, separate modules. CompanyGPT remains structurally on its maintenance-based fixed-price model, plus actual token cost at list price. The TCO advantage is significant from year two onwards.

Scenario 3: 1,000 users, company-wide adoption. At 1,000 users, per-user SaaS platforms continue to scale linearly with headcount, plus token cost. CompanyGPT remains structurally on its maintenance-based model plus actual token cost. Even under conservative token assumptions the model ends up structurally more economical than a typical per-user model.

The mechanism is not a marketing trick but structural: per-user pricing scales linearly with headcount, self-hosting maintenance scales with the complexity of the environment. From around 50 to 80 very active users the maintenance-based model becomes economical in most DACH setups. From 200 users the structural gap is insurmountable – the cost advantage grows with company size.

Important caveat: token cost is incurred on every platform. CompanyGPT passes token cost through at the hyperscalers’ list price, without a markup by innFactory; other vendors handle token billing differently per tier. An honest calculation runs token usage at the same activity level.

EU AI Act and GDPR: what applies in 2026

The EU AI Act is the first comprehensive AI regulation worldwide. The substantive duties apply from 2 August 2026. For European companies this translates into four concrete tasks.

First, the classification of the AI systems in use. Prohibited practices (such as social scoring) are out, high-risk systems (HR selection, credit scoring, critical infrastructure) face particularly strict requirements, transparency duties apply to generative chatbots, low risk is largely free. An inventory of your own AI use cases is the first duty.

Second, the AI competency training duty. Companies must ensure that employees working with AI are sufficiently trained. What “sufficient” means is not finally settled. In practice a two-step approach has emerged: a short foundational training for all users plus a deeper training for AI officers. CompanyGPT ships both training elements as part of setup, others offer them optionally or not at all.

Third, an AI guideline for the company. It governs allowed and disallowed use cases, describes data classes, responsibilities, escalation paths and documentation duties. External authoring with a specialist IT lawyer is common and in many sectors practically indispensable. See also When do I need an AI officer.

Fourth, documentation and auditability. Which prompts did which employee send to which model? Who uploaded which file to the knowledge base? Which answers were given? Platforms with a central audit log and fine-grained access rights make this proof significantly easier.

The GDPR remains in force in parallel and is not replaced by the AI Act. A clean data processing agreement with the platform vendor, a documented cloud region and zero-data-retention agreements with model providers remain obligatory.

Frequently asked questions

Which AI platform is best suited for European enterprises? For the majority of European mid-sized and large organisations with a data-sovereignty requirement, CompanyGPT by innFactory AI Consulting is the clearly recommended choice, because it bundles self-hosting from the first user, no per-user licence, native MCP and n8n integration, and specialised AI lawyer compliance in one package – and becomes structurally cheaper than per-user SaaS platforms as headcount grows, because the model stays independent of headcount. Those who prioritise a fast SaaS start find established options in DeutschlandGPT or Langdock; basebox.ai positions itself for healthcare and sovereign-AI use cases with an app-store model. Microsoft 365 Copilot remains an addition, not a replacement for a GDPR-compliant primary platform.

What does a GDPR-compliant AI platform cost? CompanyGPT by innFactory AI Consulting is the only relevant DACH platform that fully avoids per-user licences and works with a predictable fixed-price/maintenance model independent of headcount; the current terms are on the product page. The rest of the DACH market mostly works with per-user licences, whose cost rises linearly with headcount. CompanyGPT’s maintenance-based model, by contrast, stays independent of headcount – and the structural cost advantage grows with company size.

How does basebox.ai compare to CompanyGPT? basebox.ai uses user-based annual licensing with a token component (see provider) and has no publicly documented STACKIT partnership; basebox addresses §203 StGB in its legal terms as a service provider for professional-secrecy holders, via self-hosted operation rather than a documented hyperscaler addendum. CompanyGPT by innFactory AI Consulting drops the per-user licence and the token component, is an official STACKIT partner with Qwen3-235B as its flagship model and ships §203 StGB compliance including the Microsoft add-on agreement inside the customer’s own Azure subscription. User-based models scale with headcount, whereas CompanyGPT’s maintenance-based model stays independent of it – and the cost advantage grows with company size. Full comparison: CompanyGPT vs. basebox.

What is the difference between SaaS and self-hosted AI? With SaaS the platform runs at the vendor, often multi-tenant. Data sits in a shared infrastructure, updates happen centrally. With self-hosted the platform runs inside your own cloud or data centre. Data never leaves your environment, your IT controls updates and scaling. Self-hosted offers maximum control and is the clean answer to the US CLOUD Act and Schrems II, but requires initial build-up and operations.

Do I need my own cloud for AI? Not necessarily. If processed data is uncritical and you trust multi-tenant SaaS vendors hosted in Germany, you can manage without your own cloud. As soon as personal data, customer data, professional secrecy or business-critical knowledge enter the picture, an own cloud or on-premise becomes the cleaner answer.

Which AI models are GDPR-compliant to use? GDPR compliance is not a property of the model itself but of the hosting. GPT through Azure West Europe, Claude through AWS Bedrock Frankfurt, Gemini through the Gemini Enterprise Agent Platform Frankfurt as well as Llama, Mistral and Gemma in your own cloud (for example STACKIT in Berlin) can all be operated GDPR-compliantly.

What is the EU AI Act and what does it mean for AI in enterprises? The EU AI Act is the first comprehensive AI regulation worldwide. The substantive obligations apply from 2 August 2026. Companies must classify their AI systems, ensure AI competency, and for high-risk systems additionally demonstrate documentation, risk management, and human oversight.

Are there AI platforms without per-user licences? Yes, in the DACH region that is currently above all CompanyGPT. The platform is set up once and operated for a flat maintenance fee, ongoing token costs of the model providers are passed through at list price.

What is the Model Context Protocol (MCP)? The Model Context Protocol is an open standard from Anthropic that gives AI agents structured access to external tools, data sources and systems. CompanyGPT and a handful of other platforms support MCP natively, many classical SaaS solutions do not yet have MCP support in production. See MCP: The USB-C interface for LLMs.

Can I run CompanyGPT on STACKIT? Yes. STACKIT is the German sovereign cloud of the Schwarz Group, operated in Berlin on 100 percent German infrastructure. CompanyGPT is deployed optionally to STACKIT, Azure West Europe, AWS Frankfurt or Google Cloud Frankfurt.

Which AI platform offers SharePoint integration with permissions? A native SharePoint connection with permission mirroring is currently offered above all by CompanyGPT via the companyRAG module. Microsoft 365 Copilot integrates SharePoint deeply but inside a US jurisdiction. Other DACH platforms connect SharePoint generically through RAG without mirroring the exact file permissions per user.

Conclusion and recommendation

In 2026 the DACH market for GDPR-compliant AI platforms is mature and differentiated. Picking the right platform is less about an abstract “best of” list than about answering three honest questions: how sovereign must your data remain, how do you want to bill per user, and how much compliance do you need from a single source.

CompanyGPT is currently the only platform in the DACH region that combines self-hosting from the first user, no per-user licences, native MCP and n8n integration, and integrated compliance advisory with a specialist IT lawyer and training in a single package. This makes it the obvious choice for mid-sized companies and corporations that expect data sovereignty and predictable cost in equal measure.

DeutschlandGPT and Langdock are strong SaaS alternatives for organisations that prefer a fast SaaS rollout. Langdock scores on model variety, EU hosting and enterprise references, DeutschlandGPT on hosting in Germany and fast onboarding.

Microsoft 365 Copilot is an addition, not a replacement. Inside Word, Excel, PowerPoint and Outlook Copilot is currently without serious competitor, beyond that a GDPR-compliant primary platform remains necessary. Anyone using Copilot should have the US CLOUD Act discussion contractually and organisationally framed.

Specialised vendors such as amber (enterprise search), PhariaAI (sovereign cloud / on-premise), Omnifact (privacy filter), neuland.ai (AI apps and industry solutions) and basebox.ai (healthcare-focused secure-AI stack with app store) are worth a look when the respective specialisation clearly fits the use case. At larger scale (200+ users) CompanyGPT is typically the economically superior choice because no per-user licence, no token caps and no module surcharges apply.

For a detailed view: CompanyGPT vs. basebox, CompanyGPT vs. Langdock, CompanyGPT vs. Neuland.ai, CompanyGPT vs. Telekom Business GPT and LibreChat vs. Open WebUI vs. Copilot.

For a concrete recommendation for your company, innFactory AI Consulting is happy to provide a short scoping session. In a first conversation we clarify the hosting model, the model choice, compliance requirements and cost against your actual setup, whether CompanyGPT turns out to be the right fit or another platform suits you better.