Automation Workflow for Gas Utility Pipeline Safety Dig Alert Customer Communications

This workflow automates the critical, repetitive task of notifying gas customers about nearby excavation work to prevent pipeline strikes and service interruptions. It ingests dig plans from 811 systems like One Call, cross-references them with GIS asset maps and the Customer Information System (CIS) to identify affected accounts, and triggers personalized, multi-channel communications. The operational upside comes from reducing inbound call volume to damage prevention hotlines by 40-60%, lowering the risk of costly and dangerous third-party damage, and demonstrating proactive safety stewardship to regulators and the community.

Implementation requires a central orchestrator, likely built with LangGraph or a similar framework, to manage the sequence and state. It integrates via APIs with the 811 feed, the utility's GIS (e.g., Esri), and the CIS (e.g., SAP, Oracle). The architecture includes configurable approval gates for high-risk zones, exception routing for undeliverable messages, and full audit logging for compliance. Observability is built in to track notification delivery rates, customer opt-outs, and any follow-up inquiries routed to contact center agents.

This workflow automates the high-volume, repetitive task of manually cross-referencing 811 dig tickets with customer GIS data and initiating notifications. The operational upside comes from preventing service interruptions, reducing inbound call volume to damage prevention hotlines by over 40%, and improving customer perception through proactive, safety-focused communication. Savings are realized through labor deflection in call centers and field operations, while risk is controlled via automated compliance with state 'call-before-you-dig' regulations and audit-ready communication logs.

Implementation integrates with 811 systems like OneCall, utility GIS (e.g., ArcGIS), and the Customer Information System (CIS) via APIs. The Orchestrator Agent, built on LangGraph, sequences specialized agents for geospatial buffering, customer identification, and message generation. Controls include configurable risk thresholds for human-in-the-loop review of high-impact notifications and mandatory logging to a central observability platform. Rollout requires phased testing with a subset of excavation types and geographic zones to validate geospatial accuracy and message effectiveness before full deployment.

This workflow automates the high-volume, repetitive task of cross-referencing 811 excavation tickets with a geospatial customer database to identify at-risk accounts. The operational bottleneck is manual review, which delays notifications and increases the risk of third-party damage. Savings come from reducing call-center volume for damage prevention inquiries and from mitigating the cost of emergency response and repairs. The solution requires integration with 811 systems (like One Call centers), the utility's GIS for pipeline location, and the CIS for customer data and communication preferences.

Implementation occurs in three controlled phases. Phase 1 builds the core ingestion and geospatial matching engine, delivering notifications for a single high-risk county. Phase 2 integrates the multi-channel communication hub and adds an optional human-in-the-loop approval gate for sensitive areas. Phase 3 scales to full service territory and implements real-time monitoring, exception routing for data discrepancies, and integration with field crew dispatch systems for planned service interruptions. Each phase includes validation against historical dig ticket data to measure deflection rate and notification accuracy.

This workflow automates a critical but repetitive operational bottleneck: manually cross-referencing 811 excavation tickets with customer GIS data to send safety notifications. By implementing an agentic system that ingests dig plans from state One-Call centers, the solution identifies gas service lines and customers within a defined buffer of the work site. The operational upside is direct: it eliminates hours of manual data reconciliation per ticket, reduces the risk of third-party damage and associated costs, and improves regulatory compliance and customer perception through timely, accurate communication.

Implementation integrates with the utility's CIS (e.g., SAP for Utilities), GIS, and communication platforms via APIs. A primary orchestration agent, built with a framework like LangGraph, manages the sequence: data ingestion, spatial analysis, content generation using approved templates, and dispatch. Critical controls include human-in-the-loop approval gates for communications about potential service interruptions, exception routing for failed sends or customer inquiries, and full audit logging to the work ticket. Observability is built in, tracking notification volume, customer engagement, and downstream reduction in damage prevention calls.

Governance for this workflow centers on a human-in-the-loop approval gate before any customer notification is sent. A dedicated compliance agent validates the 811 ticket's proximity analysis against GIS asset buffers and internal risk models. Any alert flagged for high-risk zones, ambiguous addresses, or sensitive customers (e.g., critical care) is automatically routed to a human safety coordinator via a dedicated dashboard. This control layer ensures regulatory adherence to state one-call laws and prevents miscommunication that could lead to public safety incidents or reputational damage.

Rollout should follow a phased, geography-based pilot, starting with a single district office and non-critical excavation types. This allows for stress-testing the data integration between the 811 feed, GIS, and CIS while refining notification templates. Long-term evolution involves integrating predictive analytics to forecast dig-related service interruption likelihood and expanding the agent's capabilities to handle customer callback inquiries about active alerts. The architecture must be built on a modular orchestration layer (e.g., LangGraph) to support these iterative enhancements without a full rebuild.