Langdock Enterprise AI Gatekeeper

Langdock won early by turning AI access from a security exception into standard enterprise software. In practice that meant giving employees one approved chat window, while IT chose which of 40 plus models were available, blocked sensitive data paths, stored audit logs, and kept residency and contractual controls in place. That is why the product could spread inside regulated European companies faster than consumer AI tools.

• The product was not just a chatbot wrapper. Langdock charged roughly €20 to €25 per user for chat and agents, added separate workflow automation fees, and marked up API usage, so the wedge created a broader control layer that could expand from chat into recurring business processes.
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• Model agnosticism mattered because buyers did not want to bet their whole rollout on one lab. Langdock let admins route use cases across OpenAI, Anthropic, Google, Mistral, Meta, and others, which made procurement easier and reduced the fear of locking into whichever model looked best that quarter.
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• The closest analogue is not pure search or pure model access, but the AI workspace layer emerging between labs and incumbents. Glean came in through search and knowledge retrieval, while regional players like Adapta show the same pattern of using local trust, rollout support, and multi model access as the entry point.
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The next phase is less about letting employees ask questions, and more about making Langdock the system that governs which models run which work across the company. As governance rules tighten and AI moves into agents and workflows, the approval layer becomes the budget owner, not just the safe front end.