Energy & Sustainability
Customer Billing & Engagement
5 autonomous agents manage billing, resolve disputes, and engage customers. 55% fewer billing disputes.
Agentic AI Workflow
5 autonomous agents handle billing inquiries, outages, and energy efficiency programs
The Challenge
Billing errors and opaque charges were driving customer complaints and regulatory scrutiny
A utility with 2M residential customers processed 45,000 billing disputes annually, each costing $35 to investigate and resolve. Estimated billing (when smart meter reads failed) accounted for 8% of bills and generated 40% of complaints.
Rate structures had become so complex that customer service reps needed 15 minutes to explain a single bill. Conservation programs had 3% participation because customers received generic recommendations. The utility commission had flagged billing accuracy as a concern.
The utility needed accurate billing, proactive dispute prevention, and personalized customer engagement.
The Solution
Agents that validate meters, calculate bills, resolve disputes, advise on usage, and notify proactively
Vijan.AI deployed 5 agents. The Meter Reader validates AMI smart meter data, detecting anomalies, gaps, and communication failures before billing. The Bill Calculator applies complex rate structures with automated validation checks. The Dispute Resolver investigates complaints by correlating usage data, weather, and household patterns to explain bill changes. The Usage Advisor generates personalized conservation recommendations based on each customer's consumption profile. The Notification agent sends proactive alerts for unusual usage spikes and approaching rate tier changes.
Autonomous Agents
How each agent reasons, decides, and acts
Step 1 · Billing Inquiry
Billing Inquiry Agent
Intelligent Billing Inquiry Resolution
Responds to customer questions about charges, rate plans, and payment options using CRM and billing data, autonomously issuing credits, adjusting plans, or escalating complex disputes.
Input
Customer inquiries, billing history, rate schedules, payment records
Output
Inquiry responses, billing adjustments, payment plan approvals, escalations
- Calls CRM API to retrieve customer account details and contact history
- Calls billing database to analyze usage, charges, and rate plan eligibility
- Autonomous decision: auto-issue credits, propose rate change, or escalate to specialist
- Routes complex cases to human agents with context and resolution options
Step 2 · Outage Alerts
Outage Notification Agent
Proactive Outage Communication
Detects outages from AMI and SCADA feeds, autonomously notifying affected customers via SMS and email with ETRs, and updating them as restoration progresses.
Input
AMI last-gasp signals, SCADA alarms, customer preferences, crew ETRs
Output
Outage notifications, ETR updates, restoration confirmations
- Calls outage database for affected circuit and customer mapping
- Calls SMS gateway to send personalized outage alerts and estimated restoration times
- Autonomous decision: escalate for high-priority customers or critical infrastructure
- Routes outage resolution updates to CRM for case closure and satisfaction surveys
Step 3 · Efficiency
Energy Efficiency Advisor
Personalized Energy Efficiency Recommendations
Analyzes smart meter data to identify high-usage patterns and appliance inefficiencies, autonomously recommending rebate programs, time-of-use rates, and equipment upgrades.
Input
Hourly usage data, appliance signatures, weather, rebate eligibility
Output
Efficiency recommendations, rebate offers, TOU rate proposals
- Calls usage API to retrieve interval meter data and appliance disaggregation
- Calls rebate database to match customer usage with eligible incentive programs
- Autonomous decision: recommend HVAC upgrade, rate change, or demand response enrollment
- Routes recommendations to customer portal and email campaigns
Step 4 · Meter Support
Smart Meter Support Agent
Smart Meter Troubleshooting & Diagnostics
Responds to meter read errors, connectivity issues, and billing discrepancies by remotely diagnosing AMI health and autonomously dispatching technicians for faulty meters.
Input
AMI connectivity status, meter read errors, voltage data, customer complaints
Output
Diagnostic reports, remote reset commands, technician dispatch orders
- Calls AMI platform for meter last-read timestamp, signal strength, and error codes
- Calls ticketing API to create work orders for meters offline >48 hours
- Autonomous decision: remote reset, schedule truck roll, or escalate for investigation
- Routes resolution status to Billing Inquiry agent for customer communication
Step 5 · Demand Response
Demand Response Agent
Customer Demand Response Enrollment
Identifies high-usage customers eligible for DR programs, autonomously enrolling them, sending event notifications, and calculating incentive payments based on load reduction.
Input
Usage profiles, DR program rules, event schedules, price signals
Output
DR enrollments, event notifications, load reduction confirmations, incentive payments
- Calls demand response platform for program eligibility and event history
- Calls price API to send critical peak pricing or event-based DR alerts
- Autonomous decision: auto-enroll eligible customers, notify of events, or calculate incentives
- Routes enrollment confirmations and payments to billing and customer portal
Results
Measurable impact within 90 days of deployment
Fewer Disputes
Billing disputes reduced from 45,000 to 20,250 annually. Estimated billing virtually eliminated.
Dispute Cost Savings
Savings from reduced dispute volume and faster automated resolution (2 minutes vs. 45 minutes).
Conservation Participation
Energy conservation program participation increased from 3% to 18% through personalized recommendations.
Customer Satisfaction
Billing satisfaction improved from 2.8 to 4.1 out of 5. Regulatory concerns fully resolved.
Implementation
From pilot to production in 12 weeks
Agent Design & Tool Integration
Defined agent capabilities, connected ML model, rules engine, graph DB, and chargeback API tools. Configured orchestrator routing logic.
Shadow Mode & Autonomous Tuning
Agents ran in shadow mode on 10% of transactions. Tuned decision thresholds, tool call parameters, and feedback loop retraining frequency.
Full Autonomous Deployment
Production rollout across all channels. Agents operating fully autonomously with human-in-the-loop for critical escalations only.
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