Dispatch, quoting, and customer comms for the trade — without the constant phone-tag.
Claude triages incoming requests, quotes the routine jobs, schedules the crew, sends the right reminders, and handles the post-job follow-up — so the office isn't the bottleneck on revenue.
21 job requests handled today. Sample:
How does Anthropic (Claude) work for home services teams?
Anthropic (Claude) works for home services teams as the engine behind an Arahi AI agent built around the workflows that actually consume your week. The agent reads context from Anthropic (Claude) and the other systems your home services 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 home services team to focus on high-value strategic work. Teams typically see 24/7 after-hours and overflow coverage once the agent is in production. Setup is no-code, every action is auditable, and the agent is scoped to the rules your home services 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 Anthropic (Claude)
Authorize Anthropic (Claude) 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 Anthropic (Claude). For home services teams, this typically means routing workflows from tools like ServiceTitan alongside Anthropic (Claude).
Deploy & Monitor Results
Your AI agent goes live immediately. Track tasks automated, time saved, and accuracy metrics in real-time.
Confirmed · Tue 9 AM · gutter clean + downspout check
You're booked Tue Mar 12 at 9 AM with our team for a full gutter clean + downspout flush ($240, ~2 hrs).
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.wallace@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 job request with @Claude — match crews to availability, send a qu
- Agent11:38 AM
Confirmed sender domain DKIM is healthy.
Frequently asked questions
HVAC, plumbing, electrical, lawn care, pool service, pest control, handyman, garage door, water/fire restoration. Anywhere the office work is the constraint between dispatching trucks.
Reads the request (call transcript, web form, SMS, Yelp message), figures out the service type and urgency, checks crew availability for the area, and either books or routes to a human with all the context. 'My heat's out' on a Friday in December gets prioritized over 'thinking about a tune-up.'
Routine, well-defined jobs (drain cleaning, AC tune-up, monthly pest service) get quoted on the spot from your pricing book. Custom or large jobs (renovation, system replacement) get a quote-framework and route to your sales lead. Either way the customer sees a fast response.
ServiceTitan, Housecall Pro, Jobber, FieldEdge, ServiceTrade, Workiz, Tradify. The agent operates within your tool, not in a parallel one.
Post-job: timed review request to satisfied customers. Negative experiences route to the owner with the full context before any review prompt. The agent will not pressure dissatisfied customers for reviews — that's the failure mode it's built to avoid.
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