Sunrun resolves 50% of payment calls with Replicant conversational AI

Customer story · Energy & Utilities

How Sunrun achieved a 50% call resolution rate and 4.6/5 CSAT with AI

Sunrun, the leading US residential solar and battery provider, automated payment calls with Replicant's conversational AI, resolving nearly 50% of payment-related calls without an agent and earning a 4.6/5 CSAT score.

  • Originally published by Replicant · February 2025
  • Posted here September 13, 2026
  • 3 min read
Published by Replicant
Sunrun case study
50%payment calls resolved with no agent
4.6/5customer satisfaction (CSAT) score

About Sunrun

Sunrun is the leading provider of residential solar panels and battery storage in the United States. It specializes in renewable energy solutions that give homeowners reliable, affordable solar power, and it serves more than one million customers nationwide. The company employs more than 10,000 people and describes its offering as innovative energy experiences that bring efficiency and sustainability to the modern household.

Sunrun case study

The challenge

Sunrun was growing at a breakneck pace as demand for sustainable energy soared, and that growth created strain in its contact center. Although customers could pay online, many still chose to pay by phone. The result was a flood of repetitive calls that bogged down operations, with simple tasks such as processing a payment turning into time-consuming bottlenecks.

Those routine calls pulled agents away from the complex customer issues that needed human judgement. Costs climbed as call volumes surged, and the customer experience began to suffer. Sunrun's reputation for stellar service was at stake.

The company needed a solution that could scale as quickly as the business. Stetson Wood, its Director of Engineering over Communications, framed the goal as giving the phone channel the same quality of self-service customers experienced online, so that every channel felt seamless and intuitive. Building an AI capability in-house would have brought high costs and complexity, so Sunrun looked for an AI-powered partner that could reduce agent workloads, streamline operations and keep customers well served.

Implementing Replicant at Sunrun has pretty much paid for itself. Not only have we been able to save money with the number of agents that we have on the phone, but the service is collecting money and... we're also able to enroll customers in autopay so that there's less chance of payments not going through every month.

Stetson Wood, Director of Engineering over Communications, Sunrun

The solution

Sunrun turned to Replicant to transform how it managed payment-related calls. From day one the focus was clear: automate routine transactions so that human agents were free for more meaningful work. Replicant's conversational AI platform, designed to sound natural and act fast, was customized to Sunrun's specific needs and integrated smoothly into the company's existing workflows.

Early success with basic payment calls gave Sunrun the confidence to think bigger. Because the platform scales readily, Sunrun expanded its use cases rapidly, adding autopay enrollment, after-hours support and contract verification. It also introduced a Spanish-language option to serve its diverse customer base.

Partnering with Replicant let Sunrun avoid the cost and complexity of building an in-house AI solution and unlock operational benefits immediately. Wood notes that with Replicant the company feels it has found a partner in the AI space, rather than having to find a new vendor for every problem or opportunity that comes up. Sunrun now plans to extend its AI capabilities to SMS and web chat to improve accessibility and operational efficiency further.

Sunrun case study

The results

  • Nearly 50% of payment-related calls are resolved without any agent involvement
  • Customer satisfaction score of 4.6/5 following the automation of payment calls
  • Autopay enrollment through the AI reduced payment defaults and made paying more convenient
  • The deployment has essentially paid for itself through lower agent staffing and payments collected by the service
  • Use cases grew from payments to autopay enrollment, after-hours support, contract verification and Spanish
  • SMS and web chat are planned next to extend self-service

Get the full case study

Download the original document as published by Replicant (PDF, 2.0 MB).

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