ChatGPT Alternatives for Business: 12 Enterprise LLM Platforms Compared (2026)

76 percent of German companies that use AI rely on ChatGPT. At the same time, 66 percent name data protection as their biggest hurdle, and 93 percent would prefer an AI from Germany if they had the choice. Those are the findings of two surveys by Bitkom, the German digital industry association, from summer 2026. In other words, there is a gap between what companies use and what they actually want. And in many firms, employees have long been filling that gap with private accounts.

The good news: in 2026 there are more serious ChatGPT alternatives than ever. The bad news: most comparisons online come from vendors who put their own product in first place. This guide compares twelve enterprise LLM platforms against openly stated criteria, works out the cost per user, and covers the questions almost every other comparison skips: works councils, the EU AI Act after the Digital Omnibus, switching vendors, and access permissions on company knowledge.

What is an enterprise LLM?

An enterprise LLM (also called a corporate LLM, company GPT or internal ChatGPT) is an AI assistant based on large language models that a company licenses and manages centrally. Unlike private ChatGPT use, it comes with a contract under Art. 28 GDPR, sign-in via the company account (single sign-on), roles and permissions, logging, and a contractual commitment that inputs are not used to train the models.

The term is misleading: a company almost never trains its own language model for this. Instead, the platform uses existing models such as GPT, Claude, Gemini or Mistral and connects them to company knowledge. Which model runs behind it often matters less for the decision than where it runs, who has access to the infrastructure and how it reaches your data.

There are four basic types:

Why companies are looking for a ChatGPT alternative

Shadow AI is already reality

According to Bitkom, private AI use for work is widespread in 8 percent of German companies, occurs in individual cases in another 17 percent, and is suspected in a further 17 percent. At the same time, only 26 percent of companies officially provide AI tools to their employees. The gap is particularly large among small and mid-sized businesses: 23 percent of small companies and 36 percent of mid-sized ones do.

The problem with shadow AI is not the AI, it’s the missing framework. An employee who copies an offer containing customer data into a private ChatGPT account transfers personal data to a third party without a data processing agreement. Depending on the private account’s settings, the inputs may also be used for training. A ban alone rarely helps. What works better is an official offering that performs at least as well as the private tool.

Data protection, data sovereignty and customer requirements

The second driver is external requirements: customers in automotive, healthcare or the public sector increasingly ask in supplier audits which AI services process data and where. Professionals bound by confidentiality, such as tax advisors, lawyers or doctors, are also subject to Section 203 of the German Criminal Code. For them, a standard contract with a US vendor is often not enough.

Cost and dependency

The third driver is economic. Buying 200 licenses from a single vendor makes you dependent on its pricing and model quality. Multi-model platforms promise that you can switch to the best or cheapest model at any time. Whether that works in practice depends on the contract and on data export, as covered in the section on switching vendors.

The 12 enterprise LLM platforms compared

The table below summarizes the key criteria. Detailed profiles with strengths and limitations follow.

How we compared

We evaluated only publicly available information from the vendors: pricing pages, technical documentation, trust centers and privacy notices, as of September 23, 2026. We assessed five areas that matter for small and mid-sized businesses:

1. Data protection and sovereignty: data processing agreement, hosting location, training opt-out, vendor headquarters, certifications
2. Features: model choice, assistants, file analysis, web search
3. Cost: price per user, minimum purchase, extra costs for models or workflows
4. Integration: connecting SharePoint, Confluence and file shares, single sign-on, permission management
5. Operations: effort for your own IT, data export, termination

We deliberately don’t give an overall score. Whether a vendor is “the best” depends on which of these five areas weigh most for your company. That’s why we group vendors by use case rather than ranking them.

Which ChatGPT alternative fits you?

Answer six questions and get a reasoned recommendation with concrete next steps.

Is ChatGPT GDPR-compliant for business use?

The honest answer: it depends on the plan. Many comparison articles portray ChatGPT as non-compliant across the board. That is not accurate for the Business and Enterprise plans, and building a decision on that false assumption may rule out the solution that actually fits you.

Private accounts are off-limits for work. Business and Enterprise, on the other hand, can be used in compliance with data protection law if the data processing agreement is signed, the processing is documented in your records of processing activities, and it is clearly defined which data may be entered. That leaves the question of US access, which we cover in the section on sovereignty.

In its May 2024 guidance “Artificial Intelligence and Data Protection”, the German Data Protection Conference (DSK) summarized the criteria that apply to using LLM chatbots. They apply to every vendor in this comparison, not just OpenAI.

The vendors in detail, grouped by use case

For Microsoft 365 companies: Microsoft Copilot

What it is: Microsoft’s AI assistant that works directly in Outlook, Teams, Word, Excel and SharePoint. Since 2026 the product is simply called “Microsoft Copilot”. The basic Copilot Chat is included at no extra cost in M365 Business and Enterprise plans and works with web grounding and Enterprise Data Protection. Full integration into your documents and mailboxes costs €18.20 per user per month as Copilot Business with annual billing, on top of the M365 license.

Strengths:

• No new platform, no new login, no switching between tools
• Copilot only shows content the user can access themselves
• Prompts and responses are not used to train the foundation models
• In November 2025, the Hessian data protection commissioner found that Microsoft 365 can be used in compliance with data protection law if the conditions set out in his report are implemented

Limitations:

• Copilot is an EU Data Boundary service, but Anthropic models are currently excluded from it
• With Flex Routing, Microsoft can process requests outside the EU Data Boundary during peak loads. Administrators can turn this off. Check this setting before rollout
• Copilot ruthlessly exposes how well your SharePoint and Teams permissions are maintained. Folders shared “with everyone” will be found by Copilot for everyone

For Google Workspace companies: Gemini

What it is: Gemini is included in Google Workspace plans (Business Starter from €6.80, Standard €13.60, Plus €21.10 per user per month) and works in Gmail, Docs, Sheets and Drive. For custom agents there is also the separate Gemini Enterprise platform.

Strengths: No extra charge for the core features, prompts not used for training, data regions configurable depending on the plan, certifications to BSI C5 and ISO 42001.

Limitations: Business plans are capped at 300 users. As with Copilot, result quality depends on how tidy your Drive sharing is. And Google remains a US corporation, with all the sovereignty questions that raises.

European multi-model platforms

These platforms are the “ChatGPT alternative” most SMEs are actually looking for: an interface that feels like ChatGPT but offers several models, runs in the EU and connects company knowledge.

Langdock

The Berlin-based company runs its platform on Microsoft Azure in the EU. Users choose between models from OpenAI, Anthropic, Google, Mistral and others, most of them hosted in the EU. The Business plan costs around €25 per user per month, with a discount for annual billing. Workflows are billed separately. Langdock is certified to ISO 27001 and SOC 2 Type II, does not train on customer data, and syncs folders from SharePoint, OneDrive, Google Drive and Confluence. Single sign-on and automated user provisioning (SCIM) are included in the Business plan. Very large customers can get dedicated instances and on-premise deployment.

meinGPT

meinGPT by SelectCode GmbH from Unterhaching near Munich runs on Hetzner servers in Germany and is certified to ISO 27001:2022. The pricing model separates platform and models: the platform license starts at €18 per user for up to 50 users and drops significantly as the user count grows. A budget for model usage is added on top. Integrations include M365, SharePoint, Confluence and SAP. Alongside GPT, Claude and Gemini, open European models are available.

nuwacom

The platform from Koblenz costs €25 per user per month on the Business plan with annual billing; Enterprise starts at 20 users. It is hosted on Azure in Europe, or exclusively in Germany via STACKIT on request. nuwacom is certified to ISO 27001. Automatic knowledge base sync and DORA-compliant governance are part of the Enterprise plan, which is relevant for financial services firms.

506.ai CompanyGPT

The Austrian vendor runs CompanyGPT exclusively in the EU, in Austria on request, and is certified to ISO 27001. The pricing model combines a per-user license with a monthly flat fee for a dedicated private cloud server. The entry Enterprise plan is a flat fee for up to 50 users including SharePoint integration and single sign-on, which can be cheaper than pure per-seat models for companies of exactly that size.

Telekom Business GPT

Telekom subsidiary MMS offers Business GPT, a solution based on OpenAI models in the Microsoft cloud in Europe, including integration of company documents. For companies that prefer a well-known German contracting partner, this is an option. Keep in mind: the underlying infrastructure is Microsoft. Telekom does not publish prices.

Directly from the model maker: Claude and Mistral

Claude Team and Enterprise

Anthropic offers Claude on the Team plan for $20 per user per month with annual billing, from two users, with single sign-on and no training on your content. A premium seat with higher limits costs $100. The Enterprise plan combines a base price per seat with usage billed at API rates and adds SCIM, roles, audit logs and a compliance API. Anthropic is certified to SOC 2 Type II, ISO 27001 and ISO 42001.

The catch for European companies: no EU data residency is documented for direct use of Claude. If you want Claude with processing in the EU, you usually go through AWS Bedrock or Google Vertex AI, or through one of the platforms above. For a detailed model comparison, see our article Claude vs. GPT vs. Gemini.

Mistral Le Chat Enterprise

Mistral is Europe’s most important model maker. Le Chat costs $24.99 per user per month on the Team plan. The Enterprise plan with SAML SSO, audit logs and a white-label option is negotiated individually. What sets it apart: Mistral can run in the Mistral cloud, in your own cloud, or fully self-hosted. Connectors to SharePoint, OneDrive, Google Drive and Gmail are available, as are SOC 2 Type II, ISO 27001 and ISO 27701 certifications. According to Bitkom, however, practically no German company uses Mistral yet, even though the vast majority want European vendors.

Aleph Alpha becomes Cohere: what the merger means

Heidelberg-based Aleph Alpha was long seen as Germany’s answer to OpenAI. Since 2024 the company has no longer developed its own large foundation models and has focused on its PhariaAI platform instead. On September 16, 2026, Aleph Alpha and Canadian vendor Cohere signed their merger agreement. The combined company is to be called Cohere, with offices in Berlin and Toronto, and will run its platform on STACKIT, the cloud of the Schwarz Group. The Schwarz Group is investing around €500 million. Regulatory approval is still pending.

For companies making a decision today, this means: the “transatlantic sovereign AI” has been announced but is not yet available as a finished product for SMEs. Keep an eye on it, but don’t base your strategy on it alone.

Maximum data sovereignty: self-hosting with open models

If you want full control, combine a self-hosted chat interface with models from a German cloud or your own hardware:

• Interface: Open WebUI or LibreChat provide a ChatGPT-like interface with sign-in via LDAP, SAML or OAuth. A caveat with Open WebUI: since version 0.6.6, a license clause prohibits removing the branding for deployments above 50 users. LibreChat is MIT-licensed and has been part of ClickHouse since November 2025, but remains open source.
• Models from a German cloud: STACKIT runs its AI Model Serving in Germany, is certified to BSI C5 and ISO 27001, and neither stores inputs nor uses them for training. Available models include Llama 3.3 70B, GPT-OSS and Qwen models, billed per token. The IONOS AI Model Hub in Berlin offers a comparable OpenAI-compatible API, also with C5 and ISO 27001.
• Models on your own hardware: Above a certain volume or for professional secrecy, your own hardware can make sense. Our local AI vs. cloud AI comparison shows when that pays off.

The price of this freedom is operational effort: updates, monitoring, user management and support are on you or a service provider. Token costs, on the other hand, are almost negligible, as the calculator in the next section shows.

What does an enterprise LLM cost per employee?

List prices for most platforms range from €18 to €25 per user per month. For 50 employees that’s €900 to €1,250 a month; for 200 employees, €3,600 to €5,000. The differences between vendors are smaller than many expect. Three points that price comparisons often leave out matter more:

1. Extra costs: Some platforms bill model usage, workflows or API access separately. Ask for the total price at realistic usage.
2. Not everyone needs a license: In most companies, after a few months some staff use AI daily and others rarely. Tiered licenses or a pooled budget can be significantly cheaper.
3. Rollout costs: Training, setting up permissions, connecting knowledge and aligning with the works council cost time and money with every option and often exceed the licenses in the first year.

Run the numbers for your own situation:

Hosted in the EU or truly sovereign?

“Servers in the EU” appears on almost every vendor page. That’s not enough to assess your risk. There are three levels that differ significantly:

Why the distinction matters: in June 2025, a representative of Microsoft France stated under oath before the French Senate that he could not guarantee European customers’ data would not be handed over to US authorities. That doesn’t make levels 1 and 2 impermissible. For most everyday data, a proper data processing agreement with EU hosting is sufficient. But it does mean you should decide consciously which data may be processed at which level.

Decision guide by protection level

Many companies end up with a combination: a convenient platform for everyday work and an isolated solution for sensitive areas. That’s not a contradiction; it’s the most common architecture in practice.

Connecting company knowledge: SharePoint, Confluence and access permissions

An enterprise LLM delivers the most value when it doesn’t just write in general terms but draws on your company knowledge: manuals, contracts, product data, policies. Technically this works via Retrieval Augmented Generation (RAG): the platform retrieves relevant passages from your documents and passes them to the model together with the question.

One question is decisive for vendor selection and almost never asked in vendor comparisons: Does the platform inherit access permissions from the source system?

If you connect a SharePoint folder containing HR data to an AI platform, a sales employee asking “What does colleague X earn?” must not get an answer. Platforms handle this in one of three ways:

1. Permissions are inherited at document level: Each user only sees results from documents they can access in the source system. This is the gold standard. Microsoft Copilot works this way.
2. Permissions are set per knowledge base: An administrator defines which group may access which connected knowledge base. This works but requires discipline during setup.
3. No permission check: All users see everything that was connected. That’s only acceptable for genuinely general content.

Works council, data protection and EU AI Act: what to do before rollout

Works council: co-determination is the rule in Germany

If your company in Germany has a works council, introducing an enterprise LLM is generally subject to co-determination. Under Section 87(1) No. 6 of the German Works Constitution Act (BetrVG), it is enough that a technical system is objectively capable of monitoring employee behavior or performance. An AI platform with logging, usage statistics and chat histories meets this condition. On top of that come information and consultation rights under Section 90 BetrVG when planning technical systems.

A works agreement on AI use typically covers:

• which tools are used for which purposes
• which data is logged and who may view the logs
• that usage data will not be used for individual performance evaluation
• which training is offered
• how new features or models are handled without renegotiating every time

Involve the works council early, ideally during vendor selection. A framework agreement that covers future tools based on fixed criteria saves a lot of time later.

Data protection: the required documents

For every platform in this comparison you need at least a data processing agreement under Art. 28 GDPR, an entry in your records of processing activities and an AI usage policy for employees. Whether a data protection impact assessment is also required depends on the data processed. With HR data, health data or extensive integration of customer data, it is usually advisable. Clarify this with your data protection officer.

EU AI Act: AI literacy after the Digital Omnibus

Since February 2025, Article 4 of the EU AI Act has required companies deploying AI systems to take measures for their staff’s AI literacy. The Digital Omnibus, Regulation (EU) 2026/1744, which entered into force on July 27, 2026, softened Article 4: companies must now promote their employees’ AI literacy rather than ensure a particular level. The obligation to act remains, however. In Germany, the Federal Network Agency (Bundesnetzagentur) has been the market surveillance authority since the end of July 2026.

For rolling out an enterprise LLM, that means in practice: train employees before they use the platform and document who received which training when. A general chat assistant for writing and research is not a high-risk system under the AI Act. That can change if you use the AI for hiring decisions or credit checks. For a full overview, see our EU AI Act compliance checklist.

Switching vendors and lock-in: what to settle in the contract

After a year of use, an AI platform holds assistants, prompt libraries, connected knowledge bases and the habits of hundreds of employees. When you want to switch, you discover how much of that is tied to the platform. So clarify before signing:

• Data export: Can chat histories, assistants and prompts be exported in an open format?
• Knowledge base: Do your documents stay in your source system, or are they copied to the platform? A sync from SharePoint is easier to migrate than an upload archive.
• Model switching: Can you swap the model behind your assistants without rebuilding them?
• Open standards: Does the platform support the Model Context Protocol (MCP) and open APIs so your integrations aren’t tied to one vendor?
• Termination: What terms and notice periods apply?

The EU Data Act, in effect since September 12, 2025, helps here: cloud and SaaS customers have a right to switch providers with a notice period of no more than two months. Switching charges must be eliminated entirely from January 2027. A contract that contradicts this is a warning sign.

From shadow AI to enterprise LLM: a 90-day rollout

Most rollouts fail not because of the technology but because employees stick with their familiar private tool. A proven approach for SMEs:

Days 1 to 30: lay the groundwork

1. Take stock: which AI tools are used today, officially and unofficially? An anonymous survey gets more honest answers than a ban.
2. Classify the protection level of your data and define the appropriate level
3. Shortlist two or three vendors and request trial access
4. Involve the works council and data protection officer

Days 31 to 60: pilot with real tasks 5. Form a pilot group of 10 to 20 people from at least two departments, including today’s shadow AI users 6. Test concrete tasks, such as drafting offers, summarizing meeting notes, or answering questions about internal policies 7. Measure: how often is it used, how much time is saved, where are the problems? 8. Collect the pilot group’s best prompts in a shared library

Days 61 to 90: rollout 9. Choose the vendor, sign the contracts and the works agreement 10. Publish the AI usage policy and run training, documented for Art. 4 AI Act 11. Roll out in waves, with a contact person in each department 12. Once the official offering is in place, prohibit private AI accounts for work from a fixed date

Checklist: requirements for your enterprise LLM

Use this checklist for vendor conversations and internal alignment. It is organized by the roles involved in the decision.

Frequently asked questions about ChatGPT alternatives for business

Conclusion: the question is not whether, but which

More than half of German companies now use AI, and in many of them employees work with private accounts because there is no official offering. In 2026, the question is therefore no longer whether a company needs an enterprise LLM, but which one.

The answer comes down to three factors: your existing office suite, the protection level of your data, and your IT capacity. Price differences between vendors are smaller than the differences in data sovereignty, permission management and ability to switch. If you clarify these points before deciding, involve the works council early and train your employees, you get a tool that is actually used, rather than another license that costs money without being used.