How Service Businesses Can Use AI to Double Their Estimate Output

Most service businesses still estimate the old way: walk the job, try to remember everything, sit in the truck for 30–45 minutes building the quote, and hope nothing gets missed.

Alex Boyd from Brushwork Land Clearing rebuilt that entire process using AI and now sends full estimates while he’s still talking to the customer.

Here’s the streamlined breakdown.

Step 1: Record the Conversation (Hands-Free)

Alex wears a small recording pendant during on-site estimates. It captures everything the customer says without him taking notes or staring at his phone.

He always tells customers:
“I’m recording this so I can stay present and get accurate notes. Is that okay?”
Nobody has ever said no—they want accuracy too.

Step 2: Automatic Transcription + AI Summary

When he ends the recording:

1. The audio uploads to Plaud.
2. Plaud transcribes it.
3. A custom prompt turns the entire dialogue into clean, structured sales notes.

To build that prompt, Alex simply pasted Plaud's example into ChatGPT and said:
“Make this work for land clearing estimates. Here’s what I need it to capture.”
ChatGPT rewrote it. He copied it back into Plaud. Done.

This works for any trade—plumbing, electrical, painting, landscaping, etc.

Step 3: A Custom GPT That Knows His Pricing Model

Next, those notes feed into a custom GPT trained on Brushwork’s entire pricing system:

• Base price per quarter acre
• Minimums + discounts
• Density tiers
• Terrain tiers
• Rules and exceptions
• Operator notes
• How line items should be worded for customers

Alex created it by telling ChatGPT:
“You are a custom GPT expert. Build a pricing GPT using the model below.”
He dumped in all his rules, then stress-tested outputs until the pricing was perfect.

Step 4: Full Automation Into Housecall Pro (Extreme Mode)

Basic mode is copy → paste → done.

Alex’s extreme mode removes all manual work:

• Recording ends → audio uploads
• Transcript saves to Google Drive
• Make.com watches that folder
• Make runs the transcript through:
  • GPT #1 (summary & sales notes)
  • GPT #2 (line items, descriptions, pricing)
• GPT #2 outputs everything in JSON
• Make.com parses the JSON
• Housecall Pro’s API instantly creates the estimate in the correct customer file

Result:

“The whole automation runs by just turning off the recording.”

Why It’s Better Than Manual Estimating

Alex says it outright:

“AI doesn’t forget. It’s more accurate than me.”

Benefits:

• Never misses details customers mention in passing
• No more driveway typing sessions
• 2–3x more estimates per day
• Consistent pricing regardless of who estimates
• Clean scopes + operator notes written automatically

The Pricing Model Behind the System

AI works because his model works. Here’s the simplified structure he built from 100+ documented jobs.

Brush Density (3 Tiers)

Explained to customers as:

1. Managed Forest – light underbrush removed
2. Park-Like – most saplings cleared, mature trees kept
3. As Much As Possible – everything the machine can safely take

Terrain (3 Tiers)

1. Mild – flat or easy slopes
2. Medium – moderate slopes, more machine maneuvering
3. Steep – limited safe angles, time-intensive

Pricing Structure

• Base rate per quarter acre
• Tier multipliers (e.g., +10% for Tier 2, +25% for Tier 3—his exact numbers differ)
• GPT converts internal tiers into customer-friendly language automatically

If your equipment, brush type, or terrain differ?
Your base rate changes—but the framework works anywhere.

Don’t Have Perfect Job Data? Use What You Have

Alex’s advice:

• Use invoices + scheduling data to approximate time spent
• Re-measure job areas with tools like LandGlide or OnX
• Combine photos + job durations to train your model
• Stress test everything:
  “Try to break it before you trust it.”

Bonus: Automated Social Media Content

Alex uses the same logic for content:

• Shoot a slow-mo clip
• Share it to a Drive folder
• Automation:
  • Detects new video
  • Generates a title + caption with GPT
  • Schedules posts across Instagram, TikTok, YouTube Shorts, X, Facebook, LinkedIn
  • Randomizes hashtags

Crew photos sent to a Telegram chat go through a similar system.

Just like estimating:
Human captures the real job → AI handles the repetitive tasks.

The Mindset That Makes This Work

• Use AI only as a tool to build systems
• Be direct: “Only give me the result”
• Iterate based on real outputs
• Share your process publicly—customers trust transparency
  (“People don’t buy what you do. They buy why you do it.”)

How You Can Start Today (Simple Version)

You don’t need Alex’s full automation yet. Start with:

1. Record estimates (ask permission).
2. Transcribe them.
3. Use ChatGPT to summarize notes + write scopes.
4. Begin documenting job hours, photos, and areas.
5. Build your first density + difficulty tiers.

Then later:

• Train your own pricing GPT
• Add automations
• Eventually automate end-to-end estimates

If you’re in the local service space, this is one of the highest-ROI ways to use AI right now.

Work hard. Do your best. And let AI handle the stuff humans shouldn’t.

Catch the full episode on YouTube or Spotify—and don’t forget to join the free OWNR OPS Skool and subscribe to the OWNR OPS newsletter.