TGH Tech
Case study · Self-Build · Construction and engineering

A construction company builds its own software. We make it safe to run the business on.

At Viya Constructions, three to five people who know construction build the company’s software with AI coding tools. There’s no engineering department, and nobody translating between the business and the code. It works, and it’s fast. What they couldn’t tell was whether it was safe to run a company on. This is how we closed that gap.

4 applications under reviewWeekly reviews since June 2026
Read the storyFind out if your software is safe to run on
01 · Where it started

Software that runs isn’t the same as software you can trust.

Viya’s own people build the software the business runs on. Someone who knows exactly how a rebar schedule is calculated, or how a punch list moves between an architect and a contractor, can build the software for it directly.

From the outside, the software looked finished. People logged in and the screens loaded. What you couldn’t see was whether one customer’s data could reach another’s, whether a former employee’s access really ended, or whether something the screen said was saved had actually been saved.

02 · What they asked for

Two projects and two ongoing services.

Once, then weekly

Review and raise the standard

Check everything already built, rank whatever could stop it running as a real business system, and explain the cause and the fix for each. The first review is the starting point. After that, it’s a weekly check.

Project

Build two new modules

Payroll, and a rebar schedule tool with paid access per project, approval for offline payments, and export. Built to the standard from the first line, not fixed afterward.

Project

Move to company-owned hosting

Code and hosting moved off personal accounts and outside platforms onto accounts the business owns, with access that doesn’t depend on any one person.

Ongoing

Rules and support

Turn repeat problems into rules that reach the team while they build, and be on call for decisions that are expensive to get wrong.

“An app” turned out to be several: one platform serving staff, homeowners, contractors and architects; an admin app split out with its own logins; and the two new modules we built. Working out the real size of the job is always the first step.

03 · How it runs

They build. We hold the standard.

A six-step loop, every week. The step that matters most is the last one.

  1. 1Build:The team builds on its own priorities. For payments, logins or sensitive data, they check the approach with us first.Who: Viya, with us on call.
  2. 2Review:Everything new is checked for security, customer separation, correctness, tests and release setup.Who: us, weekly.
  3. 3Report:Same day, same format. Each finding with how serious it is, why it happened, what it risks and how to fix it.Who: us.
  4. 4Clarify:Questions on the report get answered, so nobody starts fixing from a misunderstanding.Who: both.
  5. 5Fix:The team fixes things in the order the report sets. The next review checks the actual fix, not a note saying it’s done.Who: Viya.
  6. 6Lock it in:Anything that showed up twice gets an automatic check. This is the step that makes each week cheaper.Who: us.

Between reviews

We’re on call for the decisions that are expensive to get wrong. A review can’t help with these, because it comes afterward. The AI tool offers several designs with the same confidence, and picking the safe one takes experience.

For a builder without an engineering background, this is where they’re most on their own. It’s also the cheapest hour in the whole arrangement.

  • How to handle a payment that only half goes through, and refunds
  • Access rules for four kinds of user, decided before the data structure sets
  • Data imports and deletions that can’t safely run twice
  • Three reasonable-looking designs, one of which ages badly
04 · What we learned

A fix lands where it was found. The next new feature doesn’t get it.

One pattern showed up so often it’s closer to a law. A problem gets found and properly fixed. Then something new is built, like a new type of user or a second data importer, and the same problem is there, untouched. In the third review, eight of the twelve new findings were exactly this.

The fix that landedWhere it was missing
Locking accounts after repeated wrong passwordsThe homeowner sign-up
Clearing the screen when a session endsThe homeowner portal
Keeping admin pages away from non-adminsThe architect workspace
Keeping customer data out of system logsThe second data importer
Requiring tests to pass before changes go liveThe whole front-end codebase

The fixes got much better. Carrying each fix to every place it belonged did not, because that depended on memory. This is how AI-assisted building fails: not randomly, but predictably, on whatever was built last.

It’s also why rules the computer enforces held every single time, and rules that relied on memory held only until the week got busy.

05 · The blind spot

Two reviews, five days apart. Both were right.

The weekly review asks whether the code is safe, separated and tested. It doesn’t ask whether a feature does what its screen says.

July 18 · weekly review

Medium-to-low risk

No high-risk findings. The best result so far.

July 23 · feature check of one module

48 findings, 16 that should have stopped a release

Including a drawing upload that said “success” and never sent the file anywhere.

Both were true because they measured different things. Finding that out was the most useful result of the work so far. It changed what we check, not just how often. We now check both.

06 · How it unfolded

The rules went in eleven days before the first review.

June 30Rules placed in the high-risk parts of both codebases so they load automatically, plus a required review after every change.Foundation
July 11One critical: a weakness in the release setup that could have given someone full control of the live server. Overall risk: high.45 findings
July 12On the module built since, including a gap that let customer records cross.13 findings
July 18Risk down to medium-low, no high-risk findings, and the pattern named: eight of twelve new findings were fixes that hadn’t been carried across.Best result
July 2348 findings from a new kind of check, 16 of them release blockers.Blind spot
SinceThe loop runs every week. The software keeps growing, and the standard grows with it.Live
07 · Who does what

Five roles. One of them sets the pace.

We list roles, not names, because the setup is what you can copy.

RoleSideWhat they do
Review leadTGH TechRuns the reviews, writes the reports, keeps the rules, and grades last week’s fixes.
On-call engineerTGH TechThe person Viya’s builders call when something is too risky to try alone.
FixerViyaFixes findings alongside their own building work. This role sets the pace of the whole loop.
Accounts ownerViyaOwns the cloud accounts, access and email sending, so none of it depends on one person.
Decision makerViyaDecides priorities: platform fixes or new features.

Findings arrive faster than one person can fix them. Knowing that early is better than finding out in month three.

08 · Where it stands

4 applications, now under regular review.

Every result below was confirmed by checking the actual code, not by taking a note’s word for it.

4applications under regular review
0 → 540automated tests on security-critical code, which must pass before any change goes live
17database tables where customer data is now kept separate by the database itself
1 → 0ways to take control of the live server, found and closed in the first week
Said just as plainly

The work isn’t finished.

Findings are still being worked through, including the feature problems from the late check. The first phase was a floor, not a finish line.

And just as true

They still build. We never took over.

The know-how stayed inside the company, the team kept shipping at its own pace, and now someone can say, with evidence, whether it’s safe to run the business on.

More from Viya

Two other projects, same company.

Platform

ProjectSignal for Viya

The project management platform the business now runs on.

Specific AI

Bleno for Viya

14 workflows that carry the work that used to wait for a few senior people.

Your team can build it. We make it safe to run on.

If your people are already building with AI tools, the question isn’t whether it works. It’s whether anyone can tell you it’s safe.

Find out if your software is safe to run onHow Self-Build works