TopN AnalyticsRepeatable Live Status Monitoring Across CPO Partners
An eMSP platform serving multiple charge point operator (CPO) partners, each needing live visibility into their charging infrastructure's operational status.
Where things stood
Every CPO partner onboarding onto the platform needs the same fundamental thing: real-time visibility into which of their chargers are available, charging, offline, or faulted — without it, CPOs are flying blind on their own infrastructure's day-to-day operational health.
Building this capability freshly for each new CPO partner — with its own station list, its own dashboard, its own delivery mechanism — would be slow and would multiply maintenance overhead as the partner network grows.
What we built
OCPP-connected chargers feed live connector/station status into PostgreSQL.
An Airflow DAG, one instance per CPO partner, runs on a 15-minute schedule, aggregating status by station and charger type (AC/DC) in Python.
Results are delivered to each partner's dashboard via either a BigQuery-backed dashboard table or a direct Google Sheets push, depending on the partner's preferred delivery format.
How it works
TopN Analytics built a status-monitoring pattern once and has re-instantiated it across at least six confirmed CPO brands on the platform, with only partner-specific configuration changing between instances.
Each instance aggregates real-time operational status — available, charging, preparing, finishing, offline, faulted, suspended connectors — grouped by station and charger type, refreshed on a 15-minute cycle per partner.
What we delivered and learned
The core insight here is architectural, not analytical: the same underlying logic has now been proven across at least six different CPO brands with only configuration changing between instances — direct evidence of a productized, repeatable onboarding capability rather than one-off custom builds per partner.
What it's built on
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