Cold Summit Development
Preventing Costly Rework in Cold Storage Construction
$2M+ in potential rework prevented
When we ran our AI checker against a past cold storage project that had experienced costly rework, we caught exactly the issue that had caused $2 million in rework and months of project delay. That same issue type was caught proactively on Cold Summit's project before construction began.
"InspectMind helped us catch real meaningful issues. Using it early in the process is going to absolutely help out in the field."
— Aaron Bass, Director of Construction, Cold Summit Development
Overview
Cold Summit Development specializes in building temperature-controlled facilities, where design details are critical. A single mismatch in materials, insulation, or system specifications can lead to condensation, equipment failure, or structural issues that compromise the entire facility.
As Director of Construction Aaron Bass explains, "You've got the designs very detail sensitive, right? You got any kind of single mismatch and whether it's materials, insulation, the way details come together with roofing wall systems, doors—you got issues. You know, condensation, you got could have potential for frost, heating equipment failure."
The challenge: manually cross-checking thousands of pages of drawings and specifications is nearly impossible given project timelines. That's where InspectMind AI stepped in as a pilot test case.
Watch Aaron Bass Share His Experience
Hear directly from Aaron Bass about how InspectMind AI helped Cold Summit Development catch critical issues before they reached the field.
The Challenge
Cold storage facilities require extreme precision. Every detail matters—from the type of roofing membrane to the blocking materials around doors. Manual review processes are time-consuming and error-prone, especially when specifications are scattered across multiple sections of documents.
As Aaron notes, "It's almost impossible to manually cross check, you know, thousands of pages of whether it's drawing specs, really unrealistic. You know, just given the timelines, a lot of these projects are kind of put together on to, to really have, you know, the time and the ability to really do that."
The team needed a way to catch specification conflicts and material mismatches before they reached the field, where fixes cost 10x more and cause significant project delays.
Critical Issues Caught by AI
InspectMind AI identified three high-value issues that could have led to costly field rework:
1. Wood Blocking Instead of HDPE Lumber
The AI identified door details showing pressure-treated wood blocking, but Cold Summit's specifications require HDPE (plastic) lumber that won't degrade or rot in cold storage environments.
Why it mattered: This issue actually did get installed on the project and had to be ripped out. As Aaron notes, "Had we used the AI checker ahead of time, it would have absolutely caught this issue. And we could have basically got the drawings corrected to match the spec."
Impact: This was a real-world example where early detection would have prevented field rework and material waste. Significant cost savings by catching this issue before construction.
2. Roofing Membrane Specification Mismatch
The AI flagged multiple spots where drawings specified a TPO membrane for penthouses, but the specifications (hidden in the refrigeration section, not the roofing section) called for a fully adhered EPDM membrane.
Why it mattered: As Aaron explains, "I haven't installed an EPDM membrane in, you know, a decade." The penthouses are contracted out and shipped pre-assembled. If the wrong material had been shipped, it would have required re-roofing in the field—a major expense and delay.
Impact: Prevented potential field rework and material replacement costs.
3. Slip Sheet Thickness Discrepancy
The AI found slip sheet thicknesses calling for 6 mil when specifications required 10 mil. Slip sheets are critical vapor barriers in freezer construction.
Impact: While smaller than the other issues, this could have affected building performance and long-term durability.
Results & Impact
The $2 Million Lesson
On a previous cold storage project (before using InspectMind), a materials mismatch in the door specifications went undetected during plan review. The contractor paid $2 million for rework and the project was delayed for months.
When Cold Summit came to us and we ran our checker against that past project, we caught exactly that issue. Imagine if they had run this check before construction—it would have avoided $2M+ in rework and months of delay.
That experience convinced them: they now use InspectMind on every project and even updated their global spec based on our findings to prevent similar issues across all future developments.
All three issues caught by InspectMind AI were non-cosmetic—they directly affected building performance, long-term durability, and operational costs. As Aaron emphasizes, "These examples, they're not really cosmetic. They're all things that directly affect the building performance and ultimately the long-term durability and that ultimately could impact operational costs."
For Cold Summit Development, the value proposition is clear: "If I can minimize mistakes for the contractor, basically protect them from themselves in some way, you know, I'm sending them money, right? That money is going to get used somewhere else, most likely, or given back to us."
Key Takeaways
- AI caught specification conflicts hidden in non-obvious document sections
- Prevented costly field rework and material replacement
- Enabled early issue resolution before construction began
- Protected contractors from mistakes while saving project budget
"For anyone, you know, a building complex or, in our specific case, temperature-controlled facilities, this kind of AI-driven QA, QC is incredibly valuable."
Aaron Bass
Director of Construction, Cold Summit Development
St. Augustine, Florida