1.1
The graph, from your existing views
StreamSight uses your diagrams and documentation to build process context as nodes, edges, bindings, and sub-diagrams.
1.2
Diagnose end to end
Plain-language symptoms open an investigation that traces the graph, pulls the tag history that matters, and names every id along the way.
1.3
Computed answers
A Python sandbox executes correlations, regressions, change-point detection, and spectral analysis, whatever the question calls for.
1.4
Findings become live views
Investigations end as dashboards, with KPI tiles and trend charts wired to your tags and refreshing on their own timers.
1.5
Engineers make the call
Changes arrive as reviewable proposals, and plans open before multi-step work runs, so your engineers make the operational decisions.
1.6
Bind nodes to live data
Bind to a PI System tag, a derived expression, or a synthetic source, so the diagram updates live while development keeps moving.
1.7
Status at a glance
Profiles convert thresholds to green, amber, and red, so operators and the agent read the same state.
1.8
Drill into sub-systems
Any node opens into its own sub-diagram, so a single symbol can hold a whole skid.
1.9
A shared process library
Reusable shapes, tags, and edge types keep hundreds of diagrams consistent as the model grows.
1.10
Corrections that persist
Tell it once to use the redundant sensor after maintenance, and the lesson resurfaces whenever it is relevant.