A dual-layer architecture designed for maximum privacy and minimal infrastructure costs. Train in the cloud, run entirely on-premise.
Traditional AI requires you to upload thousands of sensitive tickets to the cloud. **OTAI does not.** By using your `QueueSpec` (queue names & descriptions), we generate synthetic data to train a model that understands your specific terminology—without ever seeing a single real ticket.
Training is based on taxonomy metadata only.
Zero PII (Personally Identifiable Information) leaves your server.
Our platform consists of three main pillars that work in harmony to deliver high-precision routing with zero infrastructure complexity.
Training in the Cloud (EU)
Generates thousands of synthetic training samples from your QueueSpec metadata. No real tickets required for training.
Inference on your Server
A lightweight Docker container that hosts your custom model. Runs in your network, no internet connection required.
Ready-to-use Plugins
Seamlessly connects your ticketing system (Zammad, OTOBO, Jira) with the OTAI Runtime.
No ticket content leaves your network for either training or inference. Only queue names and descriptions are used for training.
Our task-specific models are optimized to run on standard CPU clusters. No expensive AI infrastructure needed.
Logs, confidence scores, and raw model outputs are stored directly in your systems for full compliance.
Once the model artifact is downloaded, the runtime operates in completely isolated server environments.
Predictable pricing. Scale when you need it. Cancel anytime.
Custom solutions for large scale enterprises with full SLA support and priority handling.
We've optimized our models to run on your existing infrastructure. No need to purchase expensive A100/H100 GPUs or invest in high-performance computing clusters.
Compatible with
