From telemetry and calls to a task for your team.

The preview checkpoint is a multiresolution forecasting model also trained on Splunk observability metrics. Evaluate it using your metric history while respecting format and resolution. Check errors by horizon: it does not itself include alarm rules or diagnosis for your network.

Define labels matching operational symptoms, services and equipment. Evaluate short tickets, duplicates and queries with multiple issues. Your application combines categories with assignment rules and retains original records to review ambiguous cases or team corrections.

Retain call and ticket identifiers from audio intake. Transcribe with an ASR model and use text to prepare contact reasons or summaries. Preserve the file link; distinguishing speakers requires a specific capability or an additional stage.

Your application can expose an authorised tool querying the relevant API. The model requests the call; the integration validates inputs, executes the query and returns the result. Distinguish this read from operations that change configuration or data and need other controls.

Measure the whole workflow: context retrieval, model response and external-system calls. Test concurrent queries and tool failures. A fast model does not remove operational API delays; use results to size capacity and define how support continues.

Estimate volume and concurrency per task: queries, ticket classification and tool-enabled agents. Context and workflow stages affect capacity requirements. Test one incident type or channel and compare total cost, including retrieval and integration with your systems.

Your integration can use available APIs or exports to supply context and query results. The model does not connect by itself: your application exposes authorised tools, validates inputs and executes calls. Preserve service, customer or ticket references as the task requires.

Test concurrency and latency across the complete workflow, including external tools. Distinguish interactive responses from tasks that can be queued and define how to continue after failures. Size deployment using those results and review capacity as traffic changes.

Measure category accuracy, usefulness of proposed steps, resolved queries and escalation needs. Review tool errors and conversation continuity. Compare equivalent incidents with the current workflow to assess whether the solution helps customers and the operations team.