Commercial contractors generate enormous amounts of project data. Daily reports document field conditions. Timecards capture labor. Estimates define planned scope. Accounting systems track cost. Project-management platforms record changes, schedules, and documentation.

The problem isn’t the absence of data. The information often remains disconnected until someone manually realizes something has gone wrong.

“Commercial contractors don’t need another dashboard. They need earlier visibility into operational signals that put project profitability at risk.”

To make the concept realistic, I designed the product around Summit Commercial Coatings, a fictional commercial painting contractor.

The primary persona was Alex Morgan, Director of Operations.

“Which jobs need my attention today?”

The next design question was not simply whether the AI was correct, but whether the user could inspect the reasoning.

Supporting evidence included five daily reports, fourteen site photographs, crew time records, the original scope, and project specifications.

“Success is not how often someone talks to the AI. It is whether the right information reaches the right decision-maker early enough to change the outcome.”

“Instead of asking ‘Do you trust the AI?’, the interface asks: Does the evidence support this conclusion?”

The product does not claim that the $13,159 has been recovered. It clearly states that recovery remains potential until the contractual change process advances.

I tested the clickable prototype with four participants across five tasks: identify the highest-risk project, understand Riverside’s risk, validate the evidence, prepare and internally approve a PCO, and use Copilot to investigate portfolio-level risk.

Three participants completed all five tasks and described the workflow as very easy. One retired operations manager with lower familiarity with modern digital interfaces completed two tasks, made wrong turns in the middle of the flow, and could not complete the Copilot task.

Because the sample was small, I treated the 85% task-completion rate as directional qualitative evidence — not a statistically meaningful performance metric.

What Testing Changed

• Evidence Review — Strengthened human-decision wording and clarified the transition to preparing a PCO draft.
• Action Review — Changed the approval language to “Approve Internal PCO” so users would not confuse internal review with contractual approval.
• Copilot — Changed the navigation label from “Copilot” to “Ask Copilot” to make the feature’s purpose more explicit.

The final interface uses an Industrial Intelligence visual system inspired by the environments FieldOps supports — work sites, safety equipment, and industrial materials, not a typical SaaS dashboard.

That direction wasn’t the starting point. Left to its own defaults, AI generation pulled toward purple and blue — a palette that reads as generic tech SaaS, the same look as a hundred other dashboards, with none of the grounded, on-the-job feel this product needed. Commercial contractors live in concrete, steel, and safety orange, not gradient-purple software chrome. I moved the palette to 60% concrete neutrals, 30% steel/charcoal, and 10% functional orange for actions — with semantic red/amber/green layered on top for risk states — so the interface would feel like it belonged in the world it was actually built for.