Zammad

AI Attribute Classification for Zammad

Custom model for your Zammad groups — Full On-Prem training on your GPU, on-prem inference, zero ticket export.

  • Custom model trained on your exact Zammad group definitions
  • Classify other attributes (priority and more) and ticket summaries
  • On-premise inference — no ticket content leaves your network
  • Full On-Prem trains on your GPU from your helpdesk setup — inference stays on-prem; ticket content never leaves your infrastructure.
Integration Flow

How It Works with Zammad

Step 1

Define Your Groups

Provide your Zammad group names and short descriptions as a short setup list — no real tickets needed.

Step 2

Train Your Model

Full On-Prem trains on your GPU from setup descriptions — nothing leaves your infrastructure. Inference stays on-prem; ticket content never leaves. Typically same-day.

Step 3

Deploy On-Prem

Install OTAI Runtime Core via Docker Compose. Load your signed model artifact — inference runs entirely in your network.

Step 4

Go Live & Monitor

The Zammad Connector Plugin reads new tickets and writes routing decisions back. Monitor confidence scores and retrain when needed.

Custom Model Training

Custom Models for Attribute Classification

Full On-Prem trains and runs on your GPU — air-gap capable. Nothing leaves your infrastructure, not even setup data.

Full On-Prem Path

Your Infrastructure (On-Prem)
GPU required
OTAI Studio

Configuration for subscriptions and model delivery on your side

Zammad

New tickets arrive for AI processing

OTAI Runtime + Connector GPU required

Local training and inference on your GPU — air-gap capable

Tickets Enriched by AI

Classification, priority, and fields updated automatically

No ticket data leaves your network. Full On-Prem trains entirely on-prem — nothing leaves, not even setup data. Inference always runs on your infrastructure.

AI Capabilities

Fields AI Can Improve in Zammad

OTAI doesn't just route to Group — it can classify and populate multiple Zammad fields automatically.

Group

Group Assignment

Automatically assign tickets to the correct Zammad group based on content analysis

Priority

Priority Classification

Set ticket priority (1-5) by analyzing urgency signals in subject and body

State

Status Prediction

Predict initial ticket state based on request tone and complexity

Tag

Auto-Tagging

Apply relevant tags from your taxonomy automatically

Object Attribute

Custom Field Population

Fill custom Zammad object attributes with AI-extracted values

Requirements

Zammad 6.0+ (self-hosted or managed)
Docker / Docker Compose for OTAI Runtime
API access with admin token
2 CPU cores, 4 GB RAM minimum

Common Zammad Setups

Pre-built setup templates to get started quickly with Zammad.

1

IT Helpdesk

1st/2nd/3rd Level, Hardware, Software, Network, Access Management

2

Customer Service

Billing, Returns, Shipping, Product Questions, Complaints

3

Municipal Services

Citizen Requests, Permits, Infrastructure, Public Safety

ROI Estimate

See Your Potential Savings

Example monthly savings from replacing manual ticket routing with OTAI. See the full page for the assumptions behind these figures.

Quick ROI Estimate

See how much Zammad can save you

Small team (50 tickets/day)€3,500
Mid-size (200 tickets/day)€13,600
High volume (750 tickets/day)€54,500

estimated monthly savings vs. manual routing

See full ROI examples
Pricing

Editions

Free Cloud Trial to evaluate. Full On-Prem: from ~€500 / month (software, agent-based), on request — quote depends on agents + pack (Entry / Standard / Premium).

Free Cloud Trial

Evaluate & test

Free
  • Routing, priority, multi-field AI + summaries
  • No field-count limit
  • Hosted Free Cloud Trial — runs online, not on your servers
  • Built to evaluate before Full On-Prem
  • Community support
Available Now

Full On-Prem

On request · agent-based software

From ~€500 / month
  • Routing, priority, multi-field AI + summaries
  • Unlimited values per field
  • Quote depends on agents + pack (Entry / Standard / Premium)
  • Run on your own GPU — bring your own or optional appliance
  • Requires a GPU with at least 24 GB VRAM
  • Fully isolated — nothing leaves, not even setup data
  • Maximum data sovereignty & compliance
  • Support & updates included
View Product

Frequently Asked Questions

Common questions about using OTAI with Zammad.

Ready to automate classification
for Zammad?

Get a custom model trained on your Group definitions. Same-day turnaround, on-prem deployment.