Quote, design, finance, and install — chased through one agent.
Reads each new inquiry, calculates savings from the customer's bill, proposes the right system size, books the site assessment, and tracks the install through commissioning.
9 quotes drafted today. One sample summary:
How does OpenAI (ChatGPT) work for solar energy teams?
OpenAI (ChatGPT) works for solar energy teams as the engine behind an Arahi AI agent built around the workflows that actually consume your week. The agent reads context from OpenAI (ChatGPT) and the other systems your solar energy operation depends on, runs the routine work in the background, and surfaces only the cases that need a human decision. Automate repetitive tasks and free up your solar energy team to focus on high-value strategic work. Teams typically see higher pre-qualified appointments once the agent is in production. Setup is no-code, every action is auditable, and the agent is scoped to the rules your solar energy team defines — not a generic template applied to your business.
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Read the trigger event and pull the contact's context
- 2Draft the message in your team's voice
- 3Cite each personalized line's source
- 4Queue for your review or auto-send by confidence
Get started in three steps
Connect OpenAI (ChatGPT)
Authorize OpenAI (ChatGPT) in your Arahi AI dashboard. The secure connection takes less than 60 seconds.
Configure Your AI Agent
Set up triggers, actions, and conditions specific to how your team uses OpenAI (ChatGPT). For solar energy teams, this typically means routing workflows from tools like Aurora Solar alongside OpenAI (ChatGPT).
Deploy & Monitor Results
Your AI agent goes live immediately. Track tasks automated, time saved, and accuracy metrics in real-time.
Your solar quote · 8.2 kW · est. 22-yr return
Based on your last 12 months ($186 avg monthly bill, mostly summer-loaded), an 8.2 kW system covers ~94% of usage.
Personalized using LinkedIn activity from the last 30 days.
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Marco11:42 AM
Approved the draft to m.delgado@homemail.com.
- Agent11:41 AM
Drafted the email and queued it for review.
Reason: High-confidence personalization but recipient is C-level — escalating per policy.
- Agent11:40 AM
Pulled LinkedIn activity and HubSpot deal context.
- Agent11:40 AM
Triggered: Reply to every solar inquiry with @ChatGPT — calculate savings from the utility
- Agent11:38 AM
Confirmed sender domain DKIM is healthy.
Frequently asked questions
Aurora Solar, Energy Toolbase, Sighten (now SunRun), and direct CRM (Salesforce, HubSpot). Design tools integrate for proposal generation.
From the customer's last 12 months of utility bills, local solar irradiance, and your current panel/inverter pricing. Estimates are within ~5% of formal proposals.
It walks customers through cash, loan, and PPA options based on their situation. Substantive financing decisions go through your finance team.
It tracks the permit and interconnection status, sends customer updates at each milestone, and flags delays with your operations team.
Yes — it watches each install's production data and proactively notifies customers of issues. Maintenance plans are managed through the same channel.
Explore more AI agent solutions
Start automating Solar Energy for OpenAI (ChatGPT)
7-day free trial. Works with the tools you already use.