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Langdock

productivity
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GDPR-compliant AI workspace for enterprise teams - connects Claude, GPT-4o, and Gemini to company data with custom AI assistants and organization-wide usage analytics.

Langdock is a European AI workspace platform that provides enterprise teams with a multi-model chat interface, custom AI assistant builder, and data source integrations - all hosted on GDPR-compliant EU infrastructure with SOC 2 Type II certification. Founded in 2023 by Max Klimmek and Robert Seidel in Berlin, the company is backed by Cherry Ventures and delivers access to Claude 3.5, GPT-4o, Gemini 1.5, and other models from a single workspace with centralized billing, usage analytics, and role-based access control. Teams use Langdock to build department-specific AI assistants with custom instructions and connected data sources including Confluence, Notion, Slack, and Google Drive, so the AI has relevant company context without employees finding and pasting context manually. Administrators see per-user and per-department token usage, which models are being used, and which queries are most frequent - providing AI adoption visibility that individual ChatGPT or Claude accounts cannot offer.

#ai-assistant
#enterprise
#privacy
#productivity
#llm
#gdpr
Freemium

Free plan available

Update Tool
langdock.com
Freemium
Pricing Model
Productivity & Workflow
Category
2023
Since
Free Plan
Access

Key Features

  • Multi-model access provides Claude 3.5, GPT-4o, Gemini 1.5, and Mistral from a single workspace with no separate API key management per model for end users
  • Custom AI assistants with instructions, knowledge base connections, and assigned tools let teams deploy department-specific agents for HR, legal, engineering, and support
  • Data source integrations with Confluence, Notion, Slack, Google Drive, and SharePoint give AI assistants real-time company knowledge without manual context pasting
  • Admin analytics dashboard shows per-user and per-department model usage, token counts, and query frequency to track AI adoption and costs across the organization
  • GDPR-compliant EU data hosting with data processing agreements and no AI training on user prompts - required for enterprises under European data protection law
  • SOC 2 Type II certification and SSO integration with Okta, Azure AD, and Google Workspace for enterprise security and identity management requirements
  • Usage policies and model restriction settings let administrators limit which models different employee groups can access and set prompt guardrails per assistant type

Use Cases

  • European enterprise teams adopting AI that must keep company data in EU-hosted infrastructure under GDPR data processing agreements before using any AI product
  • HR teams building an internal Langdock assistant connected to Confluence HR documentation so employees can ask policy questions without escalating to HR staff
  • Engineering managers using usage analytics to track AI productivity gains and justify AI tool spend to finance with per-team token cost breakdowns
  • IT administrators deploying Langdock as a managed AI workspace instead of employees using personal Claude or ChatGPT accounts with uncontrolled data exposure

Pros

  • GDPR-compliant EU hosting with no training on prompts is the key differentiator for European companies where ChatGPT and Claude.ai do not meet legal requirements
  • Custom assistants connected to Confluence and Notion give team AI access to company-specific knowledge - general model access alone cannot replicate this context depth
  • Admin analytics provide organization-wide AI usage visibility that no individual model subscription offers - necessary for enterprise AI governance and cost management

Cons

  • Model selection lags direct provider interfaces by days or weeks - teams that need cutting-edge models on release day may find Langdock roster updates too slow
  • Building custom assistants with accurate retrieval from large document sources requires ongoing curation of knowledge base content to keep assistant answers current
  • Pricing scales with seats and usage - large organizations with high per-user AI consumption may find Langdock more expensive than direct API access with custom tooling

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