There’s a silent killer on construction projects—and it's hiding in the specifications.
Division 26, Division 28, general conditions, addenda, submittal requirements—they all contain layers of language that can easily contradict each other or be misinterpreted across roles. The result? Change orders, disputes, incorrect procurement, delays in prefab, and blown labor budgets.
These are the “gotchas.”
They’re not just mistakes. They’re the surprises that come back to bite you after decisions are made. The wrong cable type in the wrong location. The disconnect between plan notes and equipment mounting heights. The spec section that contradicts the cut sheet. The feeder identified for copper in one section and aluminum in another.
They’re also incredibly hard to catch—until now.
With [IQ], project teams can prompt the AI to uncover these landmines early in the project lifecycle—before estimating is finalized, before prefab is locked, and before the field team is left holding the bag. [IQ] becomes not just a reviewer, but a cross-disciplinary interpreter of risk.
This is where AI earns its place in construction—not by replacing people, but by removing the blind spots that cost people time, money, and confidence.
With [IQ], contractors don’t need to wait until something goes wrong to react. They can now:
This is the new preconstruction advantage. Not just to see what's there—but to anticipate what’s missing.
Specs are no longer a liability buried in fine print. They become an asset—an active source of truth that can be reviewed, questioned, and clarified.
And as AI continues to evolve, the contractors who learn to spot these “gotchas” early will be the ones leading the charge—not chasing RFIs, but shaping the project with foresight and precision.