Langdock pricing 2026: plans, hidden costs, and ROI comparison

Langdock positions itself as a secure, enterprise-ready AI platform with transparent starting prices. On paper, €20 per user per month looks straightforward. In practice, Langdock’s pricing spans multiple cost layers, including per-user licenses, workflow run packages, and AI model usage, with an additional surcharge.

For teams rolling out AI across departments, this structure forces the budget to increase gradually. Costs scale with headcount and automation volume, not with resolved outcomes or business impact. That makes forecasting difficult as adoption grows.

This guide breaks down Langdock’s pricing exactly as published, highlights the hidden cost drivers most buyers overlook, and explains when per-user pricing starts to work against you. We will also look at why outcome-based pricing models, like Workativ’s, often stay more predictable and cost-effective at scale.

Langdock is an enterprise-focused AI platform designed to help organizations deploy secure internal AI chat assistants and workflows for employees. It allows teams to interact with company knowledge, documents, and tools through AI while maintaining strong governance and access controls.

The platform is primarily designed for internal use cases such as knowledge discovery, internal support, and employee productivity. Langdock emphasizes security and compliance, offering features aligned with requirements such as SOC 2, ISO 27001, and GDPR, making it appealing to regulated and security-conscious organizations.

Langdock’s commercial model reflects this enterprise focus. Pricing combines per-user licensing for chat and assistants, separate workflow automation packages, and usage-based AI model costs, creating a multi-layered structure that can become complex as adoption and automation scale across teams.

Teams compare Langdock with Workativ before finalizing the price, since the two platforms follow very different pricing philosophies as AI adoption scales.

Langdock’s pricing is anchored around per-user licensing, with additional costs for workflows and AI model usage. While this structure works for controlled, internal rollouts, costs tend to rise with headcount and automation volume, making long-term budgeting harder as more teams and use cases are added.

Workativ is often evaluated alongside Langdock because its pricing is better aligned with actual usage and outcomes than with seats. Teams can scale automation without licensing every employee, making it easier to forecast spend, justify ROI, and avoid the budget drift that commonly appears with per-user AI pricing models.

At first glance, Langdock’s pricing appears simple. A per-user subscription for AI chat, optional workflow packages for automation, and usage-based API pricing for AI models. In reality, the total cost is shaped by how these layers interact as adoption and automation expand across teams.

To understand what Langdock really costs in 2026, each pricing component needs to be viewed separately, and then together.

Langdock pricing at a glance

Langdock’s pricing is structured across three core layers: Chat and Assistants, Workflows, and API usage. Each layer introduces a different cost driver, which together determine the final spend.

Chat and Assistants: base subscription

The Chat and Assistants layer forms the foundation of Langdock’s pricing and follows a per-user subscription model. Langdock offers a 7-day free trial with no credit card required, allowing teams to test internal AI chat before committing.

The Business plan is priced at €20 per user per month, excluding VAT, and supports up to 1,000 users. This tier includes enterprise access controls such as SSO, SCIM, and SAML. For organizations planning larger deployments, the Enterprise plan shifts to custom pricing and typically includes options like dedicated deployments and enhanced support.

Workflow automation add-on pricing

Workflow automation is priced separately from the base subscription, adding an additional cost layer. Langdock uses a package-based pricing model per workspace, per month, based on the number of workflow runs.

Lower-tier packages include approximately 2,500 workflow runs per month, execution logs, and a 30-day retention period. Higher tiers, such as the Business workflow package, are priced at €449 per workspace per month and include up to 40,000 workflow runs. These packages cover execution volume, but they do not include AI model usage.

API pricing: usage-based pricing with a surcharge

Langdock’s API provides unified access to multiple AI models and is billed based on actual usage. In addition to the underlying model provider's costs, Langdock applies an approximate 10% surcharge.

As workflows and assistants rely more heavily on AI models, API usage becomes a significant contributor to overall spend. This creates a third pricing meter that scales independently of users and workflow run limits.

How these pricing layers add up

Langdock’s total cost is influenced by three variables: the number of users, the volume of workflow automation, and AI model consumption. While each component is clearly defined on its own, costs can rise quickly as adoption spreads across departments and automation use cases increase.

Why Langdock’s per-user pricing gets expensive as teams scale

Langdock’s base pricing starts at €20 per user per month on the Business plan. While this looks reasonable for small teams, costs increase linearly with headcount. For example, onboarding 250 employees already translates to €5,000 per month, and at 1,000 users, the base subscription alone reaches €20,000 per month, before adding workflows or API usage.

As adoption expands across departments, every additional user adds a fixed recurring cost regardless of how frequently they use the platform or whether the AI delivers measurable outcomes for their role. When workflow automation is added, teams also pay €449 per workspace per month for up to 40,000 workflow runs, plus separate AI model usage billed via the API with an additional surcharge. This multi-layered structure compounds quickly at scale.

In contrast, Workativ does not price based on the number of employees. Teams can roll out AI agents across the organization without licensing every user upfront, allowing costs to scale with actual usage and automated outcomes rather than headcount. For growing organizations, this difference often results in budgets that are significantly more predictable and cost-effective over time.

While Langdock’s pricing page clearly outlines its plans, many teams underestimate how quickly total costs can add up once AI adoption moves beyond a small pilot. The biggest challenge is that spend is driven by multiple pricing meters rather than a single, outcome-based metric.

Per-user scaling is the biggest budget leak

Langdock’s base pricing scales directly with headcount. Costs increase as more employees are onboarded, regardless of how often they use the platform or how much value they generate. As AI adoption expands across departments, budgets can grow rapidly, even when ROI remains uneven across roles and teams.

Workflow automation introduces a second cost meter

Workflow automation is priced separately from the core subscription and is based on per-workspace tiers tied to workflow run volume. This means teams are not only paying for users, but also for how frequently automations are executed. As more internal processes are automated, costs rise even if the number of users stays the same.

AI model usage becomes a third layer of spend

In addition to users and workflow runs, AI model usage is billed separately under Langdock’s API pricing. Workflow executions consume model tokens, and Langdock applies an additional surcharge on top of the underlying model provider’s rates. As automation becomes more AI-driven, this usage-based cost can quietly become a significant part of the monthly bill.

Unused value and rollover limitations

Workflow run allowances are reset monthly and do not roll over. If usage fluctuates, common in real-world operations, teams risk paying for capacity they don’t fully use, leading to value leakage over time.

Langdock’s total cost is rarely defined by a single line item. In practice, spend is shaped by how broadly the platform is adopted, how deeply automation is used, and how intensively AI models are consumed across the organization.

Active user count

Even moderate increases in user adoption raise costs linearly at €20 per user per month, making headcount growth the most direct and predictable driver of spend.

Department-wide rollout velocity

As Langdock expands beyond early adopters into HR, IT, finance, and operations, user counts rise quickly—often faster than teams anticipate during initial budgeting.

Number of workflow workspaces

Each workspace carries its own monthly package cost. Adding new automations or teams often means creating more workspaces, not just running them more often.

Workflow execution volume

Higher automation usage increases the need to move into larger workflow tiers, raising monthly costs even if user counts remain unchanged.

AI model consumption via API

Workflows and assistants consume AI tokens billed separately through API usage, with an added surcharge on top of model provider rates.

Security and enterprise configuration needs

Dedicated deployments, custom security controls, or enterprise support arrangements can further increase total contract value.

Langdock comes loaded with powerful features, including integration, chat, AI, workflows, actions, and more. Let’s get a full picture of these features. 

1. Internal AI chat: Secure AI chat for employees with document uploads, controlled web search, and internal knowledge access.

2. Custom AI assistants: Create governed AI assistants with defined instructions and connected knowledge sources for internal use cases.

3. Workflow automation: Trigger structured actions through APIs and OpenAPI specifications to automate internal processes.

4. Unified AI model API: Access multiple AI models through a single API layer, simplifying model routing and management.

5. Enterprise security and access control: Supports SSO, SCIM, and SAML with role-based access and compliance-aligned governance.

6. Usage monitoring and logs: Provides visibility into user activity, assistant usage, and workflow execution logs.

Let’s discuss the pros and cons of Langdock’s pricing mode. 

Pros:

1. Strong security and governance: Designed for enterprise use with SOC 2, ISO 27001, GDPR alignment, and support for SSO, SCIM, and SAML.

2. Model-agnostic architecture: Allows teams to use multiple AI models through a unified API without being locked into a single provider.

3. Clear entry pricing for chat: The €20 per user per month Business plan makes it easy to estimate initial costs for internal AI chat.

4. Good fit for internal knowledge use cases: Works well for employee-facing AI chat, document Q&A, and controlled internal AI adoption.

Cons:

1. Per-user pricing scales poorly: Costs rise linearly as more employees are added, even if usage and value vary widely across roles.

2. Automation is not included by default: Workflow automation is priced separately per workspace, adding another recurring cost layer.

3. Multiple cost meters increase complexity: Total spend depends on users, workflow runs, and API usage, making budgeting harder at scale.

4. Limited visibility into outcome-level ROI: Analytics focus more on usage and logs than on cost per resolution or business outcomes.

Unlike enterprise platforms that rely on opaque quotes and long sales cycles, Workativ follows a clear, published, session-based pricing model, making costs easy to understand, forecast, and scale.

Workativ openly lists its plans:

• Magic plan ($0) – Includes a generous number of sessions with core employee support capabilities, ideal for pilots and early adoption.

• Business plan ($349/month) – Comes with higher session limits, advanced integrations, analytics, and automation features needed for production use.

• Enterprise plan (custom) – Designed for large organizations requiring compliance, RBAC, SSO, and tailored deployment, without forcing unnecessary long-term lock-ins.

The biggest difference between Langdock and Workativ shows up once teams move past initial pilots and start scaling AI across the organization. While both platforms support enterprise-grade AI use cases, their pricing models behave very differently over time, especially in terms of predictability, ROI visibility, and how costs grow as adoption increases. The following points highlight where these differences matter most when evaluating long-term pricing fit.

Predictability: per-user vs usage-based outcomes

With Langdock, pricing increases as more users are added and expands further as workflow automation and AI usage increase. This makes long-term budgeting harder, especially as adoption spreads across departments. In contrast, Workativ follows a usage- and outcome-aligned pricing approach, tying costs to actual activity and allowing teams to plan spend with clearer caps and fewer surprises.

ROI clarity

Langdock’s per-user, activity-based pricing makes it difficult to directly connect spend to outcomes, such as resolved requests or deflections. Even when usage increases, understanding the cost per interaction remains challenging. Workativ’s pricing structure makes ROI easier to track by aligning costs with measurable outcomes, such as automated resolutions and interaction volume.

Scale without budget shock

As Langdock adoption grows, costs rise automatically with seat expansion, creating budget shock when new teams are onboarded. Workativ avoids this by allowing AI agents to scale across the organization without requiring a license for every employee, enabling growth without sudden increases in recurring costs.

While both Workativ and Langdock help organizations adopt AI securely, they are built for different outcomes. Langdock focuses on governance of internal AI use, whereas Workativ is designed to drive measurable automation and ROI across business operations. The differences become clearer when you look beyond features and evaluate value delivery.

Primary value focus

Langdock delivers value through secure internal AI chat and assistants that help employees access knowledge efficiently. Workativ focuses on resolving requests end-to-end by automating workflows across IT, HR, and support.

Automation depth

Langdock supports API-driven workflows, but automation is an add-on and scales by run volume. Workativ includes native workflow automation that automates tasks, triggers actions, and reduces manual effort at scale.

Pricing-to-value alignment

Langdock’s value scales with user adoption, which can inflate costs as more employees are onboarded. Workativ aligns pricing with actual usage and outcomes, making value easier to justify as automation expands.

ROI visibility

Langdock provides usage logs and activity metrics that show adoption. Workativ goes further by tying AI activity to outcomes such as deflection, resolution rates, and cost per interaction.

Scalability economics

Langdock works best for controlled internal rollouts with predictable user counts. Workativ is better suited for teams that want to scale AI broadly without licensing every employee or triggering budget spikes.

Langdock delivers strong governance for internal AI access, while Workativ delivers higher long-term value for teams prioritizing automation, ROI clarity, and predictable scaling.

Choosing between Langdock and Workativ comes down to how you want AI costs to behave as adoption grows.

Langdock is a solid choice when the primary goal is secure internal AI access. It works well for organizations with controlled rollouts, predictable user counts, and a strong emphasis on EU data residency and governance. For teams comfortable managing multiple pricing levers users, workflow runs, and AI usage- it provides a structured way to introduce AI internally.

Workativ, on the other hand, is better suited for teams that want pricing to track real work getting done. Aligning costs with usage and automated outcomes rather than headcount, it helps avoid the budget drift that often comes with per-user models. For organizations under pressure to prove ROI through deflection, resolution rates, and cost per outcome, this approach offers clearer long-term economics.

Book a demo to see how Workativ delivers measurable employee support outcomes without the complexity of pricing.