Find where work waits in your delivery pipeline, from data you already have.
Process mining that turns your existing event logs into BPMN diagrams + bottleneck heatmaps in hours.
Enterprise process-mining suites such as Celonis are sold through sales and built for company-wide processes. For a software-delivery team, the diagnostic value of process mining (finding where lead time is actually spent) doesn't need enterprise BI: Stride mines your Stride activity, or any event log you can export as CSV or XES, into process maps and bottleneck heatmaps.
Why don't delivery dashboards show where the time goes?
Engineering leaders sense their teams are slow but can't pinpoint where the time goes. Dashboards show velocity, throughput, and cycle time, but not the wait between stages. The bottleneck is usually a specific step (code review, QA scheduling, design handoff) and dashboards don't surface which. Process mining is the right diagnostic, but an enterprise process-mining suite is a large purchase for one team's delivery pipeline.
Can Stride mine BPMN diagrams from the event logs you already have?
Stride's Optimize module mines event logs: your Stride story history (status changes, plus pull-request link, merge and close events from GitHub or GitLab) or a CSV or XES log you upload. An uploaded log becomes a process model you can open as a BPMN diagram, and a discovered map shows every path work actually took. A heatmap colours each step by how long work sits there before moving on, so the slowest steps stand out.
- BPMN process models mined from uploaded CSV or XES event logs (no manual modelling)
- Variant analysis: what % of cases follow the dominant path vs deviations
- Bottleneck heatmap: each step coloured by measured time before work moves on (red = slowest)
- Bottleneck and automation-opportunity insights with an estimated yearly cost, which you can turn into a story or an automation item
- Process simulation: what-if scenarios for proposed interventions
- Date-range filter for any period, plus an alert when median cycle time rises 20% against the previous 30 days