Full-Time
SaaS learning platform for corporate training
No salary listed
London, UK
Hybrid
Three days in office per week.
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Docebo provides a cloud-based learning platform for businesses to train employees and other stakeholders by combining formal, social, and experiential learning. It operates as a Software-as-a-Service (SaaS) product, where clients subscribe to access features like course management, social learning tools, AI-driven recommendations, and analytics. Users enroll and track training, receive personalized learning paths, and measure progress within a scalable interface that supports multiple learning modalities. Compared with typical LMS options, Docebo emphasizes integrating formal, social, and experiential learning in one system and uses artificial intelligence to tailor content and recommendations to each learner and organization. The goal is to help companies improve workforce development by offering accessible, scalable, and personalized learning experiences that boost skills and performance across their teams.
Company Size
1,001-5,000
Company Stage
IPO
Headquarters
Toronto, Canada
Founded
2005
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Paid Vacation
Employee Stock Purchase Plan
Hybrid Work Options
Remote Work Options
Docebo's MCP Server signals the MCP era - 6 musts for secure, production-ready LMS integration. The LMS is no longer just a destination interface. In July 2026, it became a callable service layer inside enterprise AI assistants, and that shift has immediate consequences for L&D, IT, and security teams. Docebo's general availability release of its MCP Server on July 22, 2026 marks a practical turning point: learning operations can now happen in ChatGPT, Copilot, Claude, and Gemini instead of only inside the LMS UI. That sounds like a UX improvement, but the deeper change is architectural. When an LMS becomes a toolset inside assistant workflows, operating models, permission boundaries, and governance controls all need to evolve. Why this release matters now. What makes this moment important is not just feature velocity, but implementation timing and enterprise readiness pressure. From Docebo's release and community rollout details, teams are moving from beta patterns into production architecture now. This includes a required move away from temporary beta endpoints to permanent server URLs and a re-authentication cycle for users. In practical terms, this is not future planning - it is active cutover work. For enterprise learning leaders, this creates a narrow window to answer three business questions: * Where should learning workflows execute - in LMS screens, AI assistants, or both? * Which actions are safe to expose to natural-language tool invocation? * How will you audit and control assistant-mediated access at scale? From LMS destination to LMS tools: the new operating model. The strongest signal in Docebo's MCP direction is the move from passive retrieval to operational actions. Current capabilities position MCP for both learner and admin use cases, including: * Learner-side access to training information, progress, and certifications * Admin-side workflows for enrollments, course and learning plan management, and content curation * AI-assisted content curation actions such as discovering third-party content, comparing options, and importing into folders This changes day-to-day L&D work in a few meaningful ways: * Fewer context switches for admins and managers * Faster completion of repetitive operations through natural language * More pressure to design role-specific tool exposure, because assistants can now execute, not just answer The key takeaway: MCP is not just another integration. It turns the LMS into a governed capability layer that can be invoked from multiple assistant surfaces. What implementation teams must get right first. The configuration flow described in Docebo's developer documentation is straightforward, but it has important constraints that affect rollout quality. Core implementation realities. * Setup is a shared responsibility between Docebo Superadmins and assistant-platform admins * OAuth app setup and MCP server setup are distinct steps * Users complete one-time authorization, but SSO-related flow limitations still require careful sequencing * Custom server architecture enables persona-based exposure of tools * The built-in learner server is fixed, while custom servers can be created, enabled, disabled, edited, or deleted Immediate rollout checklist. * Create separate OAuth apps per assistant client when needed * Standardize MCP server naming and path conventions by persona/use case * Validate production endpoint changes before user enablement * Segment assistant connectors by audience (learner vs admin) to reduce permission confusion * Run pilot tests with realistic enrollment and content-volume scenarios A notable lesson from community feedback is that error messaging clarity matters. Permission failures can present as ambiguous resource errors in assistant conversations, which creates avoidable support load if role boundaries are not clearly designed. Security and governance: what admins should demand next. MCP adoption in enterprise learning is viable only if security controls mature alongside usability. Two external signals are especially relevant: * Microsoft's enterprise MCP model emphasizes read-focused tool boundaries, delegated permissions, rate limits, and activity logging through existing governance surfaces. * The MCP enterprise-managed authorization extension formalizes centralized IdP control to reduce per-user token sprawl and improve revocation governance. * NSA security guidance highlights broader MCP risks - including weak access control patterns, token/session handling gaps, tool misuse paths, and insufficient auditability. For enterprise teams, this translates into concrete control requirements: * Centralized authorization policy via enterprise IdP * Least-privilege tool exposure by persona and environment * Strong token lifecycle controls (rotation, revocation, scope discipline) * Comprehensive audit logging tied to user identity and tool invocation context * Execution guardrails for high-impact actions and abnormal request patterns * Clear change control for tool catalogs and connector updates In short, if LMS workflows are becoming assistant-executable, then governance must shift from UI permissions alone to assistant-era policy enforcement. What comes next in the MCP era of enterprise learning. Docebo's July 2026 release shows where the market is heading: enterprise learning platforms are becoming part of a broader AI tool fabric. The winners will not be organizations that simply connect an LMS to an assistant. They will be the ones that operationalize this model with disciplined architecture, role design, reliability testing, and security-by-default controls. The strategic opportunity is clear: make learning workflows faster and more embedded in work without sacrificing control. The teams that treat MCP as both a productivity layer and a governance challenge will set the new standard for enterprise L&D execution.
Docebo, a learning management system provider, has acquired Zive, a Hamburg-based enterprise AI startup, strengthening its position in AI-driven workplace learning. The deal was announced at Docebo's Inspire conference in April. Zive specialises in knowledge retrieval technology that connects unstructured data sources across enterprises, making them searchable through AI. The acquisition enables Docebo to shift from content storage to contextual knowledge delivery embedded in employees' workflows. The integration powers Docebo's AgentHub, which uses proactive AI agents to scan internal documents, identify updates, create learning content and distribute it to relevant teams automatically. This marks a transition from reactive chatbots to autonomous AI agents that can reason and act independently. The move positions Docebo beyond traditional learning management systems towards a broader knowledge orchestration platform, particularly benefiting customer education and sales enablement teams.
Docebo, a learning platform provider, reported fourth quarter 2025 results with subscription revenue of $59.1 million, up 9% year-over-year, representing 94% of total revenue. Total revenue reached $63.0 million, an 11% increase. The company achieved net income of $26.9 million, or $0.93 per share, compared to $11.9 million in the prior year period. Adjusted EBITDA reached $13.3 million, representing 21.2% of revenue, up from 16.7% a year earlier. Annual recurring revenue (ARR) grew 8.4% to $238.1 million. Excluding its largest OEM customer and foreign exchange impacts, ARR increased approximately 12.5%. Free cash flow was $12.3 million, representing 19.6% of revenue. CEO Alessio Artuffo called Q4 "one of Docebo's strongest quarters on record", citing robust bookings performance.
Docebo shares edged higher in after-hours trading on Tuesday after the learning management software company announced the launch of a $60 million substantial issuer bid. The Toronto-based firm will offer to repurchase its own shares as part of the buyback programme, signalling confidence in its financial position and commitment to returning value to shareholders. Details about the specific terms of the substantial issuer bid, including the offer price and timeline, were not immediately disclosed in the initial announcement.
Docebo's acquisition of 365Talents: what it signals for learning and skills intelligence. Docebo's acquisition of 365Talents is a meaningful development in the learning technology and skills intelligence space. While learning platforms and skills tools have been moving closer together for some time, this deal highlights how central skills have become to learning, internal mobility, and workforce readiness conversations. We have been tracking the learning technology and skills intelligence markets for several years. Based on our research, enterprises are increasingly clear about one thing: learning can no longer be separated from skills. Organizations want learning to be driven by real skill needs and tied more directly to workforce outcomes. The Docebo - 365Talents acquisition fits well into this broader shift. Most organizations already know they have skill gaps. They run assessments, build frameworks, and generate reports. Yet, based on our research, these efforts often struggle to change how people are developed, deployed, or redeployed. Skills data frequently sits in isolation, disconnected from learning systems and talent decisions. As a result, skills initiatives become exercises in measurement rather than action. This is why interest in skills intelligence platforms has grown. Enterprises are looking for solutions that do more than describe skills, they want platforms that help them act on skills, whether through learning, mobility, or workforce planning. 365Talents' role in the skills intelligence space Based on our research, 365Talents has established itself as a strong player in the skills intelligence market, with good growth momentum and a clear focus on enterprise use cases. The platform has supported a broad range of scenarios, including: * Skills visibility, helping organizations understand what skills they have today * Learning alignment, by identifying gaps and guiding relevant development * Internal mobility and career pathing, enabling better movement of talent across roles and projects * Workforce readiness and redeployment, especially as roles evolve due to Artificial Intelligence (AI) and automation What has set 365Talents apart is its emphasis on making skills intelligence usable. Rather than treating skills as static data, the platform has focused on embedding skills insights into real decisions across learning and talent management. From Docebo's perspective, the acquisition is about more than adding a skills taxonomy or analytics layer. Docebo has been clear that it sees skills as valuable only when they are actionable. Based on our reading of the announcement, Docebo is positioning the combined offering as an AI-powered intelligence layer that connects skills, learning, and workforce readiness. The idea is to move beyond traditional course-based learning models and toward learning that is triggered by real skill needs tied to roles, projects, and business priorities. This aligns with what we are seeing across the learning technology market. Buyers increasingly expect learning platforms to: * Personalize learning based on skills and context * Measure progress in terms of capability and skill development, not just course completion. In this sense, the acquisition strengthens Docebo's ability to participate in the broader skills-based talent conversation, not just the Learning Management System (LMS) market. Open questions: learning-first or broader talent use cases? At the same time, the acquisition raises important questions. Historically, 365Talents has supported use cases well beyond learning, including internal mobility, career pathing, and workforce planning. With the platform now part of Docebo, it remains to be seen how broadly these use cases will continue to be supported over time. Docebo has indicated that 365Talents will remain a distinct product and brand in the near term, with a phased approach to integration. While this provides continuity for existing customers, longer-term priorities will matter. Will the platform continue to invest equally in mobility and career pathing use cases, or will skills increasingly be viewed primarily through a learning lens? How Docebo balances depth in learning with breadth across other talent use cases will be an important area to watch. From our perspective, this acquisition has the potential to be a positive catalyst for 365Talents. Being part of a larger learning platform provider could accelerate product development, expand market reach, and strengthen go-to-market execution. We also hope this move gives renewed impetus to 365Talents' product roadmap and Go-to-Market (GTM) efforts, especially as enterprises look for clearer, more scalable skills-based solutions. Continued investment in AI, skills inference, and real-time skill updates will be critical to maintaining momentum in an increasingly competitive market. For enterprise buyers, success will ultimately depend on execution: * How tightly skills and learning are integrated in practice * Whether skills insights genuinely drive development and mobility decisions, and * How effectively the combined offering supports workforce outcomes, not just insights The Docebo-365Talents acquisition reflects a broader market reality: learning, skills, and talent decisions are converging. Organizations are looking for platforms that help them understand skills, build them through learning, and deploy talent more effectively, all within a connected ecosystem. While questions remain around long-term focus and integration depth, this acquisition clearly reinforces the growing importance of skills intelligence as a foundation for the future of learning and workforce strategy. If you enjoyed this blog, check out our webinar deck: Future-Proofing Your Workforce: Harnessing Skills and Work Intelligence, which delves deeper into skills and work intelligence and their role in workforce redesign. If you'd like to discuss the topics of skills and talent in more depth, as well as how Docebo's acquisition of 365Talents will mean for the wider sector, contact Sharath Hari ([email protected]).