Analyze incoming tickets and assign structured, hierarchical tags instantly. No rules to maintain. Fully automated.
Try our fine-tuned model on a university helpdesk scenario. Enter a German support ticket or pick an example — the model predicts one of 20 queues and shows a confidence score. This runs live against our public university classifier.
View full demoPick an example or type a ticket, then click Classify.
Everything you need to automate ticket classification on your own infrastructure.
Dedicated model per customer and target attribute (queue, priority, category). Learns your service logic, not a rigid default.
Clear target-value descriptions are enough. EU training generates synthetic data from metadata — no production ticket export.
Signed models run locally in OTAI Core via Docker. Connectors read tickets on-site and write predictions back.
The cloud app for subscriptions, licenses, training runs, and model delivery — everything outside your on-prem environment.
No ticket uploads. Share queue names and descriptions only — Studio generates synthetic training data from that metadata.
No real tickets are uploaded — ever.
Zero PII leaves your on-premise environment.
Train, review, and deploy models on your own schedule.
OTAI models train on synthetic data — not scraped tickets or manual labels. Our Kaggle sample dataset has 90+ upvotes and 10K+ downloads.
Billing, credits, training, and deployment — full control over your model lifecycle.
Manage your subscription tier, payment method, and invoices. Upgrade from Community to Pro or Enterprise at any time.
Each plan includes a simple training limit — no credit packs or add-ons. You always know how many runs your tier allows.
Define your queues, priorities, or other ticket attributes with descriptions. Start a training run and choose your quality mode.
Once training is complete, review the accuracy score and deploy. The signed model artifact is pushed directly to your OTAI Runtime.
No data labeling. No ticket uploads. Just describe your queues and let Studio handle the rest.
Describe your queues and categories with metadata — no real tickets needed.
Studio generates synthetic data and trains a custom model in Google Cloud (EU).
Inspect accuracy scores and quality metrics before approving the model.
The signed artifact is pushed to your on-premise OTAI Runtime automatically.
Studio sits between you and the training service in Google Cloud. Your ticket system and OTAI Runtime stay entirely on your own infrastructure.
Transparency is a core value. Here is exactly what OTAI Studio will never touch.
Studio never reads or processes your ticket content. Training is based on taxonomy metadata only.
All Studio infrastructure runs in EU-region data centers. Your metadata never leaves the EU.
Your on-premise OTAI Runtime runs independently. Studio only pushes new model versions.
Connector setup lives in the OTAI Console on-prem. Studio handles only the model lifecycle.
Scoped pilot or project engagements — we configure, train, and deploy on-prem. Not self-serve yet.
Available as a Service · On Request
On-prem chatbot for internal teams — grounded in runbooks and FAQs with RAG. Data stays on your infrastructure.
Available as a Service · On Request
On-prem AI suggests FAQ articles while agents work tickets — less research, more consistent answers.
Available as a Service · On Request
On-prem RAG over your knowledge base — suggested reply drafts inside the agent ticket workflow.
Available as a Service · On Request
On-prem FAQ chatbot with RAG — consistent answers for end users, data stays on your infrastructure.
Pro: support & updates included. Enterprise: cloud-trained, no local GPU. Sovereign: fully air-gapped on your hardware. All tiers also available as a one-time perpetual license (no subscription required) — on request.
Evaluate & test
Everything to run in production
Fully air-gapped, on-premise training
Scale, SLA & largest models
Support, updates, and patches are included with Pro and Enterprise — delivered directly by the OTAI team, no third parties. The coverage levels below show what each plan includes.
Support & maintenance subscription add-on for standard coverage
Support & maintenance subscription add-on for teams that need included updates with business-hours support. Patches are not included.
Support & maintenance subscription add-on with premium SLA coverage
Support & maintenance subscription add-on for teams that need included updates, patches, and expanded support coverage with faster SLA targets.
Everything you need to keep your AI deployment running at peak performance.
Regular updates to OTAI Studio and inference engines. Stay current with the latest features and improvements.
Timely security patches for your on-premise deployment. Available with Premium tier.
Guaranteed response and resolution times. From 1 business day (Basis) to 4 hours (Premium).
Direct access to the OTAI engineering team for diagnosing and resolving deployment issues.
Guidance on model retraining, performance monitoring, and keeping your AI accurate over time.
Clear escalation procedures when critical issues arise. Direct line to senior engineers.
All implementation, integration, automation, and custom development services are delivered by our certified partners.
View Partners & ServicesRun OTAI where your data lives — on-premise or in your private cloud, on CPU or GPU.
Learn how Open Ticket AI can automate your ticket classification on-premise.
