AI Integrated into GLPI: Automate Your IT Support

What if your IT technicians could resolve tickets faster, and your users could get instant answers without having to contact the help desk? That’s what the integration of Wikit Semantics into GLPI—the world’s most widely deployed open-source ITSM solution—makes possible. In this webinar co-hosted by Wikit and Teclib’ (the publisher of GLPI), discover how generative AI is transforming IT support in practice: two use cases demonstrated, a simple architecture, and a roadmap that includes an MCP server dedicated to GLPI.

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Key Takeaways from This Webinar

GLPI is the world’s most widely deployed open-source ITSM solution, developed by Teclib’ since 2015, with full control over data and available in a sovereign cloud.
The Wikit x GLPI integration serves two complementary purposes: a support chatbot for users and a troubleshooting tool for technicians.
The user chatbot provides automated support 24 hours a day, 7 days a week: it answers Level 0 and Level 1 questions and creates tickets with automatic categorization. It is available in GLPI, Teams, WebChat, and the desktop app.
Technicians receive AI-powered assistance at every step: troubleshooting suggestions, writing assistance, and automatic knowledge base generation.
Wikit Semantics connects to existing data sources (GLPI FAQs, SharePoint, document management systems, technical documentation) to provide reliable, context-aware answers.
The roadmap calls for an MCP (Model Context Protocol) GLPI server, which will enable AI agents to query and directly manage the GLPI database: information on the asset inventory, resource statistics, and actions on assets.

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AI and GLPI: Why Is Integration a Game-Changer for IT Support?

An AI chatbot to reduce the help desk's workload and improve the user experience

The first use case is aimed at employees. Integrated directly into the GLPI interface, Microsoft Teams, or WebChat, the Wikit chatbot automatically responds to common requests ( functional questions, recurring incidents) without human intervention. It also handles ticket creation with automatic categorization, reducing the workload for technicians in classifying tickets. Users have access to round-the-clock support without having to wait for a technician to become available.

More technicians to speed up resolution

The second use case is aimed directly at IT teams. When a technician opens a ticket, Wikit Semantics analyzes the context and suggests possible solutions drawn from internal and external knowledge bases. It also assists in drafting responses and can automatically generate new knowledge base articles from resolved tickets, building up knowledge over time.

AI in GLPI: Tangible Benefits for IT Teams

The integration of AI into GLPI yields measurable results on several levels. The volume of tickets processed manually decreases significantly thanks to the automatic handling of Level 0 and Level 1 requests. Technicians become more efficient when handling complex tickets, spending less time searching for information or drafting responses. The knowledge base is automatically expanded as issues are resolved, reducing reliance on internal experts. And users benefit from 24/7 support with no wait times, regardless of the channel.

Wikit Semantics: A No-Code, Sovereign AI Platform for IT Support

Wikit Semantics integrates with GLPI without requiring any custom development, thanks to dedicated plugins. The platform is no-code, multi-LLM, and hosted in France by OVHcloud; it is endorsed by UGAP, CAIH, and RESAH. It connects LLMs to the organization’s documentation sources (GLPI FAQs, SharePoint, EDM) to provide contextualized and traceable responses.

Toward AI Agents Capable of Acting Within GLPI: The MCP Roadmap

The next step in the Wikit x GLPI integration is based on the Model Context Protocol (MCP). This universal protocol for interconnecting LLMs and third-party systems will enable AI agents to do more than just answer questions; they will be able tointeract directly with the GLPI database: view the status of the IT infrastructure, access resource statistics, and trigger actions on assets. This development paves the way for full end-to-end automation of IT processes, without human intervention.

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