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Residential DesignCamarillo, CA

A custom AI floor plan tool that recovered $4,200 per month in billable time.

Built from scratch for a residential designer in Camarillo with 40 years in practice and 1,500 plus homes drafted. Cuts preliminary plans from roughly three hours of work to under one. Production deployed on Vercel edge, with 24 California code checks and a 90 second generation pipeline.

$4,200

Per Month of Billable Time Recovered

Timeline

Roughly six weeks from kickoff to production

Investment

$18,500 build + monthly retainer for hosting and tuning

Executive Summary

A 40 year residential designer in Camarillo, charging $350 per hour, was spending three to four hours on every preliminary floor plan. At roughly four plans per month that is around $4,200 per month of his most billable time spent on a task that was repetitive and rule based. We built a custom Next.js app that lets him type or speak a brief and watch a code compliant floor plan stream onto an SVG canvas in about 90 seconds. Production deployed on Vercel edge with prompt caching active. Live at ai-plan-studio.vercel.app.

The Challenge

A senior designer was spending his most billable hours on the most automatable task.

Preliminary floor plans are the gateway to every residential design engagement. They are also rule based: setbacks, egress, separation, climate zone, CalGreen. The designer in question had drafted more than 1,500 homes and could draw the geometry in his sleep, but every plan still cost three to four hours of his $350 per hour time. At four plans per month, that is roughly $50,000 per year of billable capacity tied up in work that does not require 40 years of judgment.

Key Pain Points

  • Three to four hours per preliminary plan at $350 per hour
  • Around four plans per month, repeat task with no leverage
  • Existing floor plan tools require CAD experience and do not enforce California code
  • Off the shelf SaaS does not exist for this niche workflow
  • Outsourcing risks code compliance and the designer cannot sign drafts he did not control
Our Approach

Build the tool, do not buy a SaaS.

If a SaaS existed for this, we would have used it. None did. The right shape was a custom Next.js application with the designer's preferences and California code checks built in, paired with a streaming AI generation pipeline that produces drafts the designer can review and sign off on the same day.

11 week

Phase 1: Code constraints captured

Sat with the designer to capture the 24 California code checks he runs on every plan (CRC R310 egress, R302.1 separation, Title 24 Climate Zone 8, CalGreen). These became hard constraints in the generation pipeline.

23 weeks

Phase 2: Generation pipeline

Built a 10 phase generation pipeline (Briefing through Specification) using Claude Opus 4.7 via streamObject. Every phase is checkpointed so the designer can intervene at any step.

32 weeks

Phase 3: Output formats

Added 24x36 PDF export with title block, hand rolled DXF R12 writer with proper AIA layers, and a react three fiber 3D massing view for client presentations.

4Ongoing

Phase 4: Production

Deployed to Vercel edge with prompt caching active (proven 8,039 cached tokens per generation). Currently running in production with the designer using the tool on every project.

Implementation

What is actually under the hood.

The stack is small on purpose. Next.js 15 plus React 19 for the app, Claude Opus 4.7 for the generation, Vercel edge for hosting, pdf-lib for the PDF, a hand rolled DXF R12 writer for the CAD export, and react three fiber for the 3D massing. Prompt caching keeps cost per generation low. Every plan ships with a PRELIMINARY watermark and the BPC 5536.25 disclaimer so the licensed designer holds final review.

Next.js 15 + React 19 + TypeScript on Vercel edge
Claude Opus 4.7 via @ai-sdk/anthropic v2 with streamObject from ai v5
10 phase generation pipeline (Briefing, Site Analysis, Massing, Floor Plan, Compliance, Specification)
24 hard coded California code checks (CRC R310, R302.1, Title 24 CZ 8, CalGreen)
PDF export at 24x36 with title block via pdf-lib
DXF R12 export with proper AIA layers (hand rolled writer, no SaaS dependency)
react three fiber 3D massing view for client presentations
Prompt caching active at the streamObject layer (8,039 cached tokens proven per call)
PRELIMINARY watermark + BPC 5536.25 disclaimer on every output
Results

What changed for the business.

Preliminary plans dropped from roughly three hours to under one. The designer now produces drafts in 90 seconds, reviews and signs off in 30 minutes, and uses the recovered hours on the higher value design work that actually requires his judgment. The math works out to about $1,050 saved per plan, $4,200 per month, and roughly $136,500 per year of billable capacity recovered. The tool paid for itself in weeks.

90s

Generation Time

From brief to streaming SVG floor plan, end to end on Vercel edge

3 hrs

Saved Per Plan

Roughly four hours down to under one, including review and sign off

$4,200

Per Month Recovered

Based on $350 per hour rate and roughly four plans per month

24

California Code Checks

CRC R310, R302.1, Title 24 Climate Zone 8, CalGreen, all enforced as hard constraints

Built him a tool that turns a three hour task into a 90 second one. The math made sense, the tool works, and he is using it on every project. If you want to talk to him about it, book a call and I will introduce you.

Landon Sprangers

Founder, Landon Scales

Key Takeaways

What This Campaign Proves

  • 1When a billable hour costs $350 and the work is rule based, a custom AI tool that saves three hours per task pays for itself in days
  • 2Compliance first design (24 California code checks built in as hard constraints) lets a licensed professional trust the output enough to sign their name to it
  • 3Off the shelf SaaS rarely fits niche professional workflows. Custom AI tools become proprietary leverage that no competitor has
  • 4Streaming generation (90 seconds end to end) keeps the workflow inside a single user session, unlike batch tools that break flow
Lessons Learned

What We Learned Along the Way

  • Capturing the 24 California code checks up front was the highest leverage hour spent on the entire build
  • Prompt caching at the streamObject layer cut generation cost by an order of magnitude in production
  • Watermarking every output PRELIMINARY plus the BPC 5536.25 disclaimer protects everyone and makes the tool deployable in regulated workflows
Services Used

The Mix That Delivered These Results

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