Real Businesses.
Real Results.

The Problem

As Zebra Landscaping scaled across Edmonton, quote turnaround became a bottleneck. Assembling a full estimate — measuring irregular yard areas, pricing sod, mulch, rock, fencing and decks across different rate tiers, and accounting for site conditions — took the better part of a workday. Only senior staff could do it accurately, so their time was constantly pulled off higher-value work, and getting a competitive quote out fast enough to win a job wasn't always possible.

What We Engineered

We built a field-first web app the crew runs from a phone. Staff measure a property directly on Google Maps satellite imagery using a custom click-to-draw polygon tool — built after Google removed its own drawing controls from the Maps API — with per-zone square footage computed from Mercator-projection math. On-site photos feed Claude vision, which reads back measurements and site notes, while a spoken walkthrough is transcribed by OpenAI Whisper and folded in as context. The pricing engine holds every material, rate tier and surcharge, so the itemized total is the company's real numbers, not a guess. A finished quote syncs into Jobber through a server-side GraphQL proxy that handles OAuth refresh automatically — and a person reviews every quote before it reaches a customer.

The Problem

Across our client builds, the same pattern kept paying for itself: quoting is where trades businesses quietly lose jobs. We had built the fix as custom software more than once — for a landscaper, for a demolition contractor — and each time the win came from the same place: turn a job description into a priced, professional proposal fast, while the lead is still warm. The question was whether we could ship that pattern once, as a product any contractor could sign up for.

What We Engineered

We designed, built, and launched QuotingAI as our own multi-tenant SaaS. A contractor describes the job in plain language; the AI drafts a priced, itemized quote from the company's own pricebook and rate structure, wraps it in their branding, and sends a proposal the client can e-sign on any device — with a Stripe deposit collected at signing, so a signed quote is also a committed one. Flat-rate plans, per-company branding, billing, and trial flows are all part of the platform, and we run it end to end: hosting, monitoring, updates, and support.

The Problem

This is a second, separate build for Zebra Landscaping, and it covers one job specifically: spring cleanup and yard removal. Spring is the crunch — quote requests pile up faster than anyone can type, and the team was doing those cleanup quotes by hand. Mental math, calls back to the office, inconsistent pricing. Quotes varied by who was on-site, margins were unpredictable, and staff constantly interrupted the office mid-estimate to get numbers confirmed.

What We Engineered

We built a password-protected internal quoting tool for field staff. Staff enter a client address, trace the yard on a live satellite map, and the tool calculates square footage automatically. Sliders capture property conditions, add-ons, and discounts — and a live quote total updates in real time. When the quote is ready, one tap copies a formatted, client-ready version. A Jobber integration pushes completed quotes directly into their CRM. Pricing lives in the tool, not in anyone's head.