Enterprise AI: Comparing vendors

Enterprise AI refers to AI platforms that have been developed specifically for use in organizations - with a focus on security, data sovereignty, integration into existing systems and governance. 2026 creates a highly fragmented market: In addition to US hyperscalers, European providers are increasingly positioning themselves, focusing on data protection, local operations and industry-specific use cases.

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For companies, choosing the right corporate AI is not just a comparison of tools: It is about data strategy, security, integration capabilities and the question of whether they are more likely to rely on European specialists or globally scaling platforms.

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Enterprise AI: What's behind it?

Enterprise AI combines three levels: pretrained models (e.g. language models), platforms for orchestrating assistants and agents, and integrations into existing business processes. Many providers combine these levels, others focus clearly on one layer — such as pure model providers or “AI workspaces” for knowledge work.

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Typical fields of application of corporate AI include knowledge work (documents, emails, presentations), customer service, sales, development and internal administration. At the same time, data protection and compliance requirements are increasing — particularly in Europe, where topics such as GDPR, Cloud Act and data residency play a major role.

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Microsoft 365 Copilot: AI directly in the work process

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Microsoft 365 Copilot integrates AI directly with popular office applications such as Word, Excel, PowerPoint, Outlook, and Teams. The solution accesses Microsoft Graph — i.e. documents, emails, calendars, chats and other data in the tenant — and generates contextual content, summaries, analyses, or presentations.

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With Copilot Business, Microsoft is now specifically addressing small and medium-sized companies that already use Microsoft 365. The solution is licensed as an add-on and is available globally; it benefits from ongoing model updates (e.g. integration of new GPT generations) that Microsoft is rolling out into its Copilot products.

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Strengths of Microsoft 365 Copilot as an enterprise AI

• Deep integration with popular productivity tools (Word, Excel, PowerPoint, Outlook, Teams)
• Uses existing company data in the Microsoft Graph for personalized results
• Broad ecosystem and well-known management and security mechanisms for IT departments
• Continuous development of the underlying models and features

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Possible drawbacks/limits

• Strong commitment to the Microsoft ecosystem; companies without a Microsoft 365 strategy benefit less
• Additional license costs to the existing Microsoft 365 plan
• Data is processed in the Microsoft cloud — only partially suitable for some organizations with extremely high data residency requirements
• Governance effort: Access rights in the Microsoft Graph must be properly configured so that Copilot only uses the information that employees are allowed to see

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ChatGPT Enterprise: Diverse use cases

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ChatGPT Enterprise is the enterprise version of ChatGPT and is aimed at companies that need a powerful language model with increased security, administration and integration options. The solution offers longer context windows, higher performance, and a dedicated corporate workspace where teams can work together with a centrally managed AI assistant.

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ChatGPT Enterprise can directly access corporate data sources such as SharePoint, Google Drive, Box or other business tools via connectors. ChatGPT thus goes from a general chatbot to a corporate AI, which searches documents, summarizes content, creates analyses or generates code — always in the context of its own data and processes.

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Strengths of ChatGPT Enterprise as an enterprise AI

• Powerful generative AI for a wide range of use cases (text, analysis, code, knowledge work)
• Longer context windows with which even extensive documents, chats and files can be processed in one step
• Connectors to common business platforms and file storage devices to work directly with corporate content
• Enterprise features such as SSO, role and rights management, audit logs, and central admin console for greater governance

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Possible drawbacks/limits

• Cloud-based solution; only partially suitable for organizations with very strict data residency or on-premises operation requirements
• Strong focus on generic use cases — subject-specific workflows must be mapped using your own integrations, prompts or middleware
• Connectors and data access create additional governance costs so that only approved content is used
• Depending on the licensing model and intensity of use, costs can rise significantly if introduced very broadly

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Gemini Enterprise & Gemini on Google Workspace: AI in the Google Workspace

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Gemini Enterprise and Gemini in Google Workspace bring Google's AI directly into the daily work context of Gmail, Docs, Sheets, Slides, Drive, Meet, and Chat. Users can summarize emails, write texts, analyze spreadsheets, or have presentations created — based on the information that is already in their own workspace tenant.

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In addition, Gemini Enterprise allows you to build your own AI agents and automations that control workflows across multiple Google services. Companies can thus map recurring tasks — such as reporting, documentation or approval processes — using agentic corporate AIs, which are administered and monitored centrally.

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Strengths of Gemini Enterprise as enterprise AI

• Seamless integration with popular Google tools (Gmail, Docs, Sheets, Slides, Drive, Meet, Chat) without changing tools
• Direct access to corporate documents and communications within Workspace for contextual suggestions and summaries
• Ability to create and centrally control your own AI agents and automations based on Gemini models
• Use Google Workspace's existing security, compliance, and admin features, which facilitates rollout and governance

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Possible drawbacks/limits

• Strong commitment to the Google ecosystem; full added value comes especially when Workspace is already strategically set
• Connecting non-workspace systems (on-prem tools, specialized applications) requires additional integration work
• Requires clear guidelines and training to make good use of Gemini features and comply with data protection requirements
• In environments that use Microsoft or other platform co-lots in parallel, coordination and governance costs increase

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Langdock: EU-hosted AI platform

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Langdock is a German-language corporate AI platform that combines chat, specialized assistants, agents, and a uniform API for various models. The solution is hosted in the EU, is GDPR-compliant and allows internal documents, databases and processes to be connected to set up company-specific AI workflows and assistants.

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Langdock is priced with a business plan (including AI chat, assistants, agents) per user and month, while enterprise customers receive dedicated deployments and extended support. For pure API use, a surcharge is charged on the model prices of the underlying providers, which makes it easier to integrate different models via an interface.

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Langdock's strengths as an enterprise AI

• EU hosting and GDPR focus, interesting for data-sensitive industries
• Unified API for multiple leading models
• Support for internal documents, knowledge bases, and workflows
• Suitable for both specialist departments (chat, assistants) and development teams (API, agents)

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Possible drawbacks/limits

• Smaller ecosystem and fewer “out-of-the-box” business applications compared to hyperscalers (Microsoft, Google)
• The variety of models depends on third-party providers; the focus is less on your own basic models
• Very large, global rollouts may require additional integration work with existing tool landscapes

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KARLI: AI agents for European organizations

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KARLI is an Austrian platform that positions itself as a “corporate AI agent builder.” Companies can build their own AI agents and assistants based on text, image and voice models, tailored to internal processes, industry requirements and security requirements.

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One focus is on application scenarios in industrial environments, the public sector and critical infrastructure. KARLI highlights that models and agents are trained and maintained specifically for business requirements and thus enable a high level of adjustment to individual processes.

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KARLI's strengths as corporate AI

• Strong focus on European companies and regulated industries
• Focus on customizable AI agents, including voice scenarios
• Proximity to the project: Implementation and ongoing support from a specialized team
• Uses generative AI for text, image, and speech in integrated solutions

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Possible drawbacks/limits of KARLI

• Often a project-driven approach — can initially mean more coordination and implementation effort
• Fewer standardized mass products than Copilot or ChatGPT Enterprise
• Information on pricing models is more individual, which makes a quick budget estimate difficult

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Localmind: Local AI infrastructure under your own control

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Localmind addresses companies that want to operate AI completely locally or in their own data centers in Austria or Germany. The platform enables powerful AI models to be operated “on premise” and emphasizes data sovereignty, independence from major cloud services and detailed authorization management for users and teams.

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This model can be particularly attractive for organizations with strict compliance requirements (e.g. public sector, critical infrastructure, industries with high protection requirements) - data does not leave their own infrastructure, and integrations into existing systems can be implemented in their own IT landscape.

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Strengths of Localmind as an enterprise AI

• Fully local operation in our own infrastructure or in the data center in AT/DE
• High level of control over data flows, permissions, and infrastructure
• Designed specifically for enterprise needs and centralized management of users, teams, and rights

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Possible drawbacks/limits of Localmind

• On-premises operation requires internal infrastructure, expertise and ongoing operations
• Scaling and updates are more the responsibility of the customer than when using SaaS alone
• In 2025, a security incident became public in which, according to reports, an avoidable security vulnerability led to a data leak and services were temporarily shut down — an indication of how critical security governance is in enterprise AI and how important your own due diligence reviews remain.

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Enterprise AI: This is how companies find the right provider

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The right corporate AI is less a question of the “best tool,” but of interplay with strategy, IT landscape and regulation. In practice, a multi-stage approach has proven effective:

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First, companies should prioritize their primary use cases: knowledge work, customer service, development, administration, or specialist processes. Second, it must be clarified whether data sovereignty and local operation have the highest priority - this is when providers such as Localmind or European platforms come into focus; in heavily Microsoft or Google-centric environments, Copilot or Gemini often offer the lowest barriers to entry.

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Third, governance and security requirements should be considered early on: role and rights management, auditability, logging, model and data governance. Fourthly, a multi-vendor approach is usually worthwhile: such as Copilot or Gemini for productivity workflows, combined with a specialized corporate AI platform (Langdock, KARLI, Localmind) for internal expert assistants and automation scenarios.

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Enterprise AI: Common Questions (FAQ)

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What makes corporate AI different from “normal” AI tools?

Enterprise AI is focused on security, governance, integration, and scalability. In contrast to freely accessible AI tools, these solutions include multi-client capability, authorization concepts, logging, compliance functions and interfaces to core systems such as ERP, CRM or DMS.

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Should you commit to a corporate AI provider?

A single-vendor approach simplifies governance and purchasing, but increases dependency and can limit the speed of innovation. Many companies therefore rely on a core platform (e.g. Copilot or Gemini) plus additional special solutions (e.g. Langdock, KARLI, local platforms) as long as data flows, security and responsibilities are clearly defined.

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How important is European corporate AI?

European providers can offer advantages in terms of data sovereignty, GDPR implementation and independence from extraterritorial laws such as the US Cloud Act. For some industries, this is a strategic factor, especially when particularly sensitive data or government clients are involved.

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What are typical entry-level scenarios for corporate AI in SMEs?

Many medium-sized companies are starting with corporate AI in three areas: productivity-related assistants (e.g. Copilot/Gemini in an office context), internal knowledge assistants (e.g. based on Langdock, KARLI or similar platforms) and initial automation workflows in administration or customer service. It is crucial to start small, measure clearly and gain experience in the interaction of technology, processes and employees.

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How can risks be limited when using enterprise AI?

Important levers include clean data and rights concepts, transparency about model and data flows, clear guidelines for use, and regular audits and security tests. Security incidents — such as reported vulnerabilities with AI providers — show that even with corporate AI, no solution is “per se secure,” but that continuous governance remains necessary.

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Enterprise AI: Conclusion and Outlook

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In 2026, corporate AI will develop from individual pilot projects to a strategic component of corporate IT. European providers such as Langdock, KARLI and Localmind complement global platforms such as Microsoft 365 Copilot, ChatGPT Enterprise or Gemini — with different strengths in terms of data sovereignty, depth of integration and range of functions.

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It is important for organizations to develop a clear corporate AI strategy: Which use cases have priority? Which data is allowed where? Which platforms complement each other in a meaningful way? If you answer these questions in a structured way and gradually translate them into concrete implementations, you can increase productivity, streamline processes and meet compliance requirements at the same time.

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The KI Company helps companies define their individual corporate AI stack — from the selection and combination of suitable providers to the design of use cases to technical implementation and governance. If you would like to evaluate which corporate AI is best for your environment, you can contact us at any time without obligation.