Digital Specialist for Ticket Triage Kaseya Intelligence FAQs

Where is data processed by the Ticket Triage AI Engine?

• All data sent from Autotask PSA to the Ticket Triage AI Engine is processed within the Kaseya Intelligence platform, hosted on Microsoft Azure infrastructure inside Kaseya’s private network.

• Data remains within this controlled environment during processing. For details on geographic data residency, see Infrastructure & Geographical Zoning below.

Is the Ticket Triage AI Engine related to Microsoft Copilot?

• No. The Ticket Triage AI Engine is not related to and does not leverage Microsoft Copilot.

• The engine is built on Azure OpenAI Service under Kaseya’s enterprise agreement and operates as a fully Kaseya-managed platform. Microsoft 365 Copilot licensing is not required.

Is my data used to train AI models?

• No. Customer data is not used to train the underlying large language models (LLMs). The LLMs are owned and maintained by their respective platform providers (such as Microsoft) and cannot be trained or modified by Kaseya or its partners.

Can anyone train or modify the AI models used?

• No. The LLMs used by the Ticket Triage AI Engine can only be trained or modified by their owning platform providers. Neither Kaseya nor customers can fine-tune, retrain, or alter model weights. This design ensures model integrity, security, and compliance with provider safety standards.

Can I customize the AI Engine for my business needs?

• Direct customization of the underlying AI models is not available. Customers can influence output quality by maintaining high-quality data and aligning with Kaseya’s AI readiness guidelines. Refer to the Kaseya AI Data Maturity Guide for recommendations.

Are there limits on how much data can be processed?

• Yes. The Ticket Triage AI Engine enforces multiple safeguards to manage throughput and reliability, including rate limiting, intelligent batching for high-volume operations, and Azure OpenAI Service token limits.

How often is the AI Engine updated?

The Ticket Triage AI Engine consists of multiple evolving components:

• Underlying LLMs are updated by platform providers and promoted by Kaseya following validation.
• The Kaseya Intelligence platform layer is continuously improved.
• Domain-specific intelligence improves over time as operational data matures.

Partners are notified of significant changes through official Kaseya release communications.

Where is the AI infrastructure hosted?

• The Ticket Triage AI Engine is hosted on Microsoft Azure. Kaseya is responsible for configuring, governing, and operating all supporting infrastructure.

Does data remain in my geographical zone?

• AI inference is performed in the US-East Azure region, where Kaseya’s Azure OpenAI deployments are hosted. Data sent for inference is transient and not retained by the model provider.

• Once processing completes, results are written back to Autotask and stored in the customer’s assigned Autotask data zone. The US-East region acts solely as a processing layer.

Which AI models are used?

• The Ticket Triage AI Engine uses a dynamic, multi-model architecture designed to optimize accuracy, cost, and performance.

• All models are accessed through Azure OpenAI Service using provisioned deployments to ensure compliance with data residency requirements.

How does the AI Engine integrate with Azure OpenAI?

• Kaseya’s AI Engine connects securely to Azure OpenAI Service using Kaseya-managed credentials and provisioned deployments. The platform manages prompting, context handling, model selection, and response parsing.

How does Autotask integrate with the AI Engine?

• Autotask is a native consumer of the Kaseya Intelligence platform. When Ticket Triage features are invoked, Autotask securely sends relevant data to the AI Engine, which processes the request and returns results to Autotask.

Where is AI response data stored?

• AI-generated outputs are written directly into Autotask records and stored within Autotask’s existing data infrastructure. No separate AI-specific data store is used.

Who can access my data?

• Access is limited to authorized personnel following the principle of least privilege. Access is audited, time-limited, and customer data is fully isolated between tenants.

What security measures are in place?

• Security controls include encryption in transit and at rest, strict access controls, continuous monitoring, and a defense-in-depth architecture aligned with enterprise compliance expectations.

Is personally identifiable information (PII) processed by the AI Engine?

• Depending on configuration, data sent for processing may include information containing PII. Protections include inspection and validation layers, transient processing, and infrastructure isolation under Azure OpenAI Service agreements.

How does the AI Engine mitigate bias and misuse?

• The AI Engine applies multiple safeguards including input validation, output inspection, Azure OpenAI Responsible AI controls, and standardized prompt engineering practices.

• AI-generated outputs are advisory, and human review is recommended for high-impact decisions.

How is data poisoning prevented?

• Because customers cannot modify or train models directly, exposure to data poisoning is limited by design. Additional protections include input inspection layers and continuous output monitoring.

What should I be cautious about?

• AI-generated suggestions may contain inaccuracies or incomplete information. Always review outputs before taking action.

How can I verify AI outputs?

• Cross-check AI results with Autotask data.
• Apply human review before using or sharing outputs.
• Evaluate the potential impact of recommended actions before approval.