Automation Workflow for Autonomous Home Energy Audit Scheduling and Follow-up

This workflow automates the high-touch, repetitive lifecycle of utility-sponsored home energy audits, a process burdened by manual qualification, scheduling coordination with external vendors, and inconsistent follow-up. By deploying orchestrated AI agents, utilities can eliminate administrative bottlenecks, increase program participation rates, and systematically convert audit findings into implemented efficiency measures. The operational upside comes from labor leverage, reduced cycle times from inquiry to audit, and higher-margin upgrade sales, turning a cost-center program into a revenue-generating service.

Implementation integrates with Customer Information Systems (CIS) like Oracle CC&B or SAP for customer data, and uses an orchestrator (e.g., LangGraph) to manage state across specialized agents for qualification, vendor API integration, and communications. Critical controls include human-in-the-loop approval gates for high-value upgrade recommendations, exception routing for complex property types, and monitoring dashboards for tracking audit completion rates and conversion KPIs. The architecture must handle data privacy for audit reports and ensure reliable handoffs between utility systems and external vendor platforms.

This workflow automates the high-touch, repetitive labor of managing a residential energy audit program. It eliminates manual data entry between systems, reduces scheduling back-and-forth, and ensures consistent follow-up, directly increasing program participation rates and conversion to efficiency upgrades. The operational savings come from deflecting administrative FTEs and accelerating the audit-to-upgrade pipeline, turning a cost center into a revenue-generating service.

Implementation integrates a central orchestrator (e.g., LangGraph) managing specialized agents that interface with the CIS for customer data, external scheduler APIs for provider calendars, and document systems for report generation. Controls include human-in-the-loop approval gates for high-value upgrade recommendations, exception routing for complex property types, and full observability into audit status and conversion metrics. The architecture is designed for phased rollout, starting with qualification and scaling to full autonomous scheduling.

This workflow automates a high-touch, low-conversion process that traditionally burdens call centers and program managers. It eliminates manual customer screening, appointment coordination with third-party auditors, and disjointed follow-up. The operational upside comes from converting a cost center into a scalable growth channel, increasing audit completion rates, and creating a qualified pipeline for efficiency upgrades like heat pumps or insulation, directly impacting demand-side management goals and customer satisfaction metrics.

Implementation is phased, starting with the qualification and scheduling agents integrated with the CIS and a single audit provider's API. Phase two adds the multimodal follow-up agent and CRM integration for lead routing. Critical controls include human-in-the-loop review for complex property edge cases, audit report quality checks before customer communication, and explicit consent gates for marketing outreach. The system requires observability on conversion funnel metrics, API failure rates, and customer satisfaction scores post-audit to ensure ROI and continuous optimization.

This workflow automates the end-to-end customer journey for utility energy efficiency programs, from initial qualification to post-audit follow-up. It eliminates manual lead scoring, scheduling coordination with third-party auditors, and repetitive customer communication. The operational upside comes from increased program participation, higher conversion to efficiency upgrades, and significant reductions in administrative labor for program managers, directly improving cost-per-audit metrics and driving measurable carbon reduction goals.

Implementation begins with a pilot integrating the Eligibility Agent with the utility's CIS and a single audit partner's API. Controls include confidence scoring for automated decisions, with low-confidence cases routed to a human-in-the-loop dashboard in ServiceNow or a custom supervisor UI. Observability is built via LangGraph tracing and logging to Datadog. Phased rollout expands audit partners, adds multilingual support, and integrates with downstream contractor platforms for upgrade fulfillment, ensuring each phase delivers isolated, measurable ROI before scaling.