We trained their staff on AI. Their staff built the quoting system.
General Crane Services hires cranes and riggers across Western Australia, from metro jobs to tier-one mining sites. We trained their team on AI and automating workflows. Then their own people built an automated quoting tool, and we secured it and implemented it into their business on Azure. A quote that took days now takes minutes.
How long does it take to quote a crane job?
Minutes, now. The team enters a few details about the job and the system builds the entire quote from the company's own historical pricing, ready to send straight away. Before, a single quote could take a couple of days to put together by hand.
Crane hire quoting is genuinely hard. Every job is priced from rate schedules, shift patterns, travel, crew and equipment, and the answer is different for a metro lift, a regional job and a remote mine site. All of that used to live in spreadsheets and in people's heads. Someone had to dig out what was charged last time, rebuild the numbers line by line, and format the whole thing before it could go out. While that happened, the customer waited.
For a business quoting every day, days per quote is not a paperwork problem. It is work walking out the door to whoever answers first.
We put the job details in and the quote comes back done. What used to take days is finished before the next phone call.
The best part is who built it. We trained their people, and their people built the tool. Our job was to make it secure and stand it up properly in their own environment. That is what AI adoption should look like.
Who built the quoting system?
Their own staff did. We ran AI training with the General Crane Services team, covering how to use AI well and how to automate the workflows they run every day. Their people took that and built a working quoting tool themselves, around their own rates, contracts and way of pricing jobs. That is the part worth reading twice: the client's team built it.
This is what we mean when we say training pays for itself. The people who quote crane jobs every day know exactly where the time goes and what a correct quote looks like. Once they could use AI properly, they did not need anyone to tell them what to build. They built the thing they had always wanted.
Where did Scalify come in?
We took what their team built and made it production-ready. That meant a full security check, then implementing it into the company's own software environment on Azure, with sign-in through their existing Microsoft accounts and their data in their own database. The tool their staff built became a system the whole business runs on.
The work for General Crane Services, in order:
- AI training for their staff, on using AI well and being efficient with it
- Workflow automation training, so the team could automate the repetitive work they already do
- A security review of the quoting tool their team built
- Implementation into their own systems on Azure, with company Microsoft login and a proper database behind it
- Automated job cost reports, so the paperwork after a job moves as fast as the quote before it
A homegrown tool is a great start, but a business cannot run on something only one person can log in to. Making it secure, shared and properly hosted is the difference between a clever experiment and company infrastructure.
How does quoting work now?
A request comes in, the team enters a few details, and the system produces the full quote from historical data: the right rates for that kind of job, the crane and crew lines, the lot. It comes out in two versions at once, a clean quote for the client and an internal costing breakdown for the office, and it is sent straight away. A person reviews and approves, but nobody assembles anything by hand.
The same system now follows the job past the quote. When a job is complete, it builds the job cost report, the reconciliation of what was quoted against what actually happened, so the invoicing side of the business keeps pace with the quoting side. What used to be two slow piles of paperwork, one before the job and one after, is now one system with a person overseeing it.
What changed for the business?
Quotes go out in minutes instead of days, priced consistently from the company's own history rather than whoever happened to be quoting that day. Clients get their number while they are still deciding, the office gets its costing detail without building it twice, and job cost reports stop piling up after every job.
| Step | Before | After |
|---|---|---|
| Building a quote | Days of assembling rates by hand | Minutes, details in and the quote comes out |
| Pricing | Dug out of spreadsheets and memory | Drawn automatically from their own historical quotes |
| Quote documents | One document, reworked for each audience | Client version and internal costing produced together |
| Job cost reports | Manual reconciliation after every job | Built by the same system when the job is complete |
| Access and security | Files on shared drives | Company Microsoft login, own Azure environment, own database |
Could this work for other businesses that quote?
Yes. Any business where quoting means rebuilding the same pricing logic by hand, hire companies, fabricators, service contractors, can have quotes produced from its own historical data in minutes. And any business with capable people can do what General Crane Services did: learn to use AI properly, build the first version themselves, and bring us in to make it secure and real.
We run the training that starts it and the implementation that finishes it. The middle part, knowing your business best, was always yours. We go deeper on both in automate quoting and corporate AI training.
Common questions
Did General Crane Services staff really build the quoting system themselves?
Yes. After the AI training, their own people built a working quoting tool around their contracts, their rates and the way they actually price jobs. Scalify then checked it for security, hardened it and implemented it into the company's own environment on Azure, with company sign-in and a proper database behind it.
Is the quoting fully automatic?
The heavy lifting is. The team enters a few job details and the system builds the whole quote from the company's own historical pricing, ready to send straight away. A person still looks it over and approves it, so nothing goes out the door unchecked.
How was the system secured?
It runs inside the company's own Azure environment, behind their existing Microsoft sign-in, with their data held in their own database. Scalify reviewed the tool for security before it went live and set it up so nothing sits outside the business.
What is a job cost report and does the system handle it?
A job cost report, or JCR, is the reconciliation done after a job is complete: what was quoted, what actually happened, and what should be invoiced. The same system now builds these when a job wraps up, so the paperwork at the end of a job moves as quickly as the quote at the start.
Updated 29 July 2026
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