Choose the documentation you need. Explore API references, implementation guides, and best practices.
Integration layer for OTOBO, Znuny/OTRS, and Zammad. Setup, connectors, automation rules, API, and troubleshooting.
On-prem ticket classification. Tag schema, output format, multilingual behavior, backlog tagging, hardware sizing, and evaluation.
Create the technical user and import the restricted Generic Interface webservice.
Environment variables and connectors for OTOBO, Znuny, and Zammad.
Self-service portal for subscription, licenses, and model training.
Install the open-source Zammad MCP Server for Claude, Cursor, and typed Zammad ticket tools.
Open-source internal AI chat for Zammad — LibreChat plus the MCP server, in the cloud or fully on-prem.
Insights, updates, and articles from the team.
What GPU VRAM you need for on-prem ticket AI, how hardware and API costs compare, and what Open Ticket AI runs locally — classification, summaries, Full On-Prem.
![Znuny-LLM: A Practical Guide to Self-Hosted AI for Znuny [2026]](/_astro/ticket-system-ai-on-premise-platform.D-iZlxu-.png)
Explore Znuny-LLM features, deployment choices, security controls, and rollout considerations for service desks evaluating self-hosted AI.
![Best Ollama Model for Zammad AI: On-Premise LLM Guide [2026]](/_astro/zammad-ai-hero.C0UUzIJ2.png)
Which Ollama model works best for Zammad 7 AI? A practical, on-premise model guide — the structured-output gotcha, real speed numbers, VRAM sizing, and which local LLM to pick for summaries, title rewriting, and classification.
