SolarCare AI Agents - Post Installation Support & Resolution

Solar businesses rely on referrals for growth, making customer support essential. Our AI Solution automate diagnostics, resolve common issues, and escalate only when human intervention is needed.

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Inspiration

The inspiration for this project comes from my experience working as a project manager in the solar business, where I witnessed firsthand the daily challenges faced by customer service and operations teams. They spend countless hours handling repetitive support cases, manually checking system data, coordinating across departments, and responding to frustrated customers. The workload is high, the processes are repetitive, and emotions often run high on both the customer and employee sides. This inspired us to build an AI-powered support solution that automates repetitive troubleshooting, streamlines issue resolution, and allows teams to focus on higher-value work while delivering a better customer experience.

What it does

Our solution introduces a multi-agent (A2A) UiPath automation system that transforms solar post-installation support by automating the full lifecycle from customer complaint to resolution or escalation. Both Solar Intake Agents (Built via UiPath Agent) & Diagnosis Agents (Built via Cursor & Gemini), work together to understand customer issues, perform automated diagnostics and guided troubleshooting, then either resolve the case or escalate it to a human agent with complete context.

How we built it

  • Solar Intake Agent: Understands customer requests and creates a structured support ticket. (UiPath Agent)
  • Solar Diagnosis Agent: Enables self-diagnosis (eg: system reboot, data validation) to auto-resolve cases or escalation, reduce engineer involvement. (External Agent - Built with Cursor & Gemini)
  • Human In The Loop: Complex cases are automatically escalated to human support with all diagnostic context attached.
  • UiPath Maestro orchestrates the end-to-end workflow, coordinating AI agents, API integrations, and human handoff.

Challenges we ran into

  • This was our first experience working with UiPath and building an AI agent-driven workflow.
  • Translating real-world solar support processes into a structured automation design was challenging, as much of it was previously handled manually and varied across cases.
  • Given the complexity of post-installation support, we had to make deliberate trade-offs on scope and priorities within a limited timeframe, focusing on what mattered most to deliver a working end-to-end solution.

Accomplishments that we're proud of

  • Managed to turn a real industry problem into an AI automation workflow.
  • Saw a clear transformation from a manual process to a structured automation flow.
  • Feel excited by the impact and potential of the solution we have built.

What we learned

This project helped us bridge the gap between real-world operations and automation design. We learned to break down complex manual processes into structured workflows with external customized integration.

What's next for SolarCare AI Agents - Post Installation Support & Resolution

  • Proactive: Shift from reactive to proactive monitoring by moving from complaint-based support to continuous system monitoring that detects anomalies before customers report issues.
  • Scalability. This solution is able to scale across multiple domain such as EV Charging, Smart Building Management and others.

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