
Berlin, Germany
2023
Enterprise Software, Technology, Financial Services, Healthcare, Manufacturing, Energy
Langdock is an enterprise AI software company that provides a model-agnostic platform for organizational AI adoption. Its software gives employees and technical teams a common environment for accessing large language models, working with company knowledge, creating AI agents, and automating workflows. Rather than developing its own foundation model, Langdock provides an enterprise layer connecting multiple AI models, data sources, tools, and users, with deployment and governance options designed for organization-wide use.
Langdock helps organizations provide employees with controlled access to generative AI while consolidating capabilities that might otherwise be spread across separate tools. Users can interact with different AI models through Langdock Chat, create specialized agents for recurring tasks, connect internal knowledge and business applications, and build automated workflows.
For technical teams, Langdock also provides APIs for integrating models, agents, embeddings, and organizational knowledge into existing software. The platform supports enterprise-wide AI deployment with centralized administration, including deployment within a customer’s cloud or on-premises infrastructure for organizations requiring greater control over their data and AI environment.
Langdock’s technology is built around a model-agnostic generative AI architecture rather than a single proprietary large language model. Organizations can access models from providers including OpenAI, Anthropic, Google, Mistral, and others, allowing different models to be selected for different tasks.
The platform combines LLM access with retrieval-augmented generation (RAG), AI agents, workflow automation, and enterprise integrations. Internal knowledge can be connected through integrations and vector databases, while the API supports embeddings, semantic search, document retrieval, and knowledge-based AI applications.
Langdock Agents can combine instructions and organizational knowledge with external tools and actions. The platform supports the Model Context Protocol (MCP), REST APIs, Agent-to-Agent connections, custom RAG implementations, and external vector databases.
For infrastructure control, Langdock offers multi-tenant and single-tenant SaaS as well as customer-cloud and on-premises deployment options. This allows larger organizations to place the AI application layer closer to their existing data, identity, security, and infrastructure environments.
Langdock represents an emerging part of the AI ecosystem focused not on building larger foundation models, but on making multiple AI models usable across enterprises. As organizations adopt generative AI, they increasingly need ways to connect models with internal knowledge and applications while managing access, deployment, and governance.
Langdock addresses this layer by combining employee-facing AI tools with agents, workflow automation, integrations, and enterprise infrastructure controls in one platform. Its interoperability is particularly relevant because organizations can connect different model providers, internal systems, RAG architectures, and external tools rather than building their AI environment around a single model vendor. Langdock reports more than 10,000 customer organizations and 100,000+ monthly active users as of its current press materials.
Langdock Chat provides employees with a common interface for using multiple AI models in everyday work. Users can work with documents, search the web, access company knowledge through integrations, and use generative AI across departments including sales, marketing, HR, finance, engineering, and operations. Its central distinction is model-agnostic AI access, allowing organizations to make multiple models available through one controlled workspace.
Langdock Agents are configurable AI assistants designed for recurring organizational tasks and specialized workflows. Organizations can provide agents with custom instructions, files, company knowledge, integrations, and actions. Agents can be shared across teams and accessed through Langdock, Slack, and Microsoft Teams. They also support MCP for connecting external tools and services.
Langdock Workflows provides AI-powered workflow automation for processes that require multiple steps or repeated execution. Workflows form part of Langdock’s broader platform alongside Chat and Agents, allowing organizations to move from individual AI interactions toward repeatable automated business processes.
The Langdock API gives developers a unified interface for multiple AI models and enterprise AI services. It includes completion, embedding, agent, and knowledge-folder APIs, supporting use cases such as text generation, reasoning, semantic search, RAG, custom agents, and document processing inside existing applications.
Langdock is designed primarily for enterprise knowledge work and business-process automation. Employees can use its AI chat for research, writing, document analysis, internal knowledge retrieval, and everyday assistance, while organizations can create specialized agents for repeated tasks.
Its integrations and workflows extend those applications into sales, marketing, HR and recruiting, finance, engineering, IT, and operations. Agents can search organizational information, interact with connected applications, and perform actions within business processes. The platform is also applicable to organizations with stricter data and infrastructure requirements because deployments can be managed as SaaS, placed within a customer’s cloud environment, or operated on-premises.
Langdock is model-agnostic and provides access to models from multiple providers rather than requiring organizations to use a single Langdock foundation model. Its API and platform support models from providers including OpenAI, Anthropic, Google, and Mistral.
Yes. Langdock can connect AI applications with organizational knowledge through integrations, knowledge folders, RAG architectures, vector databases, and custom APIs. Its Chat product can also search internal information through connected company systems.
Yes. Langdock Agents can use native integrations and external tools, including connections built through the Model Context Protocol (MCP). MCP servers can expose tools that Langdock converts into actions available to agents.
Yes. In addition to hosted SaaS options, Langdock supports deployment in a customer’s own cloud environment and on-premises deployment using Kubernetes-based infrastructure for qualifying enterprise deployments.
Yes. The Langdock API provides programmatic access to AI models, embeddings, agents, and organizational knowledge. Developers can use these capabilities for applications involving generation, reasoning, semantic search, RAG, and specialized AI agents.
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