Business Process Management (BPM) in solar operations remains fragmented: work orders live in CMMS, performance data sits in SCADA historians, and financial reporting happens in spreadsheets. GreenBridge BPM unifies these workflows through AI agents that automate ticket creation, prioritization, and resolution tracking with quantified revenue impact.
The operational reality for most solar IPPs and asset managers is a patchwork of disconnected systems. A performance anomaly detected in the monitoring platform requires manual investigation, then manual work order creation in the CMMS, followed by manual dispatch, and finally manual verification that the issue was resolved. Each handoff introduces delays, errors, and lost context.
GreenBridge BPM introduces agentic AI workflows that bridge these gaps. When the performance analysis agent detects an anomaly — say, a 3% specific yield drop across a string group — it automatically correlates the finding with weather data, inverter telemetry, and historical patterns. If the root cause is identified (e.g., a failing string fuse or inverter MPPT tracking issue), the agent generates a work order with specific diagnostic steps, required parts, and an estimated revenue recovery value.
This revenue-quantified prioritization is transformative. Instead of processing work orders in FIFO order or by simple severity ratings, maintenance teams can see that fixing Inverter A-12 at Site 3 recovers $450/day while replacing a broken panel at Site 7 recovers $12/day. This data-driven prioritization alone typically improves annual energy yield by 0.5-1% across a portfolio.
The BPM platform also automates compliance and reporting workflows. Monthly owner reports, regulatory filings, and warranty claim documentation are generated automatically from operational data, reducing administrative overhead by 40-60% and eliminating the errors that come with manual data aggregation.