How We Work

Example 1: Cost Estimating (Our In-House Service)

When a developer, owner, or GC needs a number before committing to full preconstruction, we deliver a Rough Order of Magnitude (ROM) estimate with a structured written report. It covers key cost drivers, assumptions, major exclusions, and a defensible cost range — enough to support a Go/No-Go decision without a long engagement. No retainer, no lengthy process.

What We Do

Why It Matters

Getting a credible number fast changes the conversation. Clients and GCs can make a Go/No-Go call before spending on full design and estimating — or present a range to ownership, lenders, or partners with confidence. The report is formatted to communicate clearly, not just to hold numbers.

Example 2: AI Tool Recommendation

A GC's preconstruction team was spending hours every bid cycle manually leveling subcontractor bids across trades — comparing inconsistent formats, chasing scope gaps, and making judgment calls without a clear framework. They'd heard AI tools could help but had no way to evaluate which were credible, which actually fit their workflow, and what real pricing looked like. We've done hands-on testing with firms that do exactly this work. We assessed the team's process, matched them to the right tool, and facilitated the relationship — including preferential pricing through our existing connection with a vendor that provides these services.

The Situation

The Value

Submittal review time dropped significantly. The team caught spec deviations earlier in the process, reducing back-and-forth with the engineer. The structured checklist output became part of the standard submittal log.

Example 3: AI Training & Team Upskilling

A GC's team was curious about AI but had no internal guidance. Different people were experimenting on their own — inconsistently, with plenty of skepticism and unanswered questions. There was no shared understanding of what tools applied to which tasks, or why. We embedded with the team and ran structured, hands-on training sessions built around their actual workflows: estimating, bid analysis, spec review, submittal coordination. Not generic demos — real tasks, real tools, real questions answered in the room.

The Situation

The Value

Skepticism turned to confidence. The team developed a shared, consistent approach to AI — knowing which tools applied to which tasks and why. Adoption stuck because it was built around real work, not a generic demo. We stayed on as an ongoing point of contact, making sure questions got answered as new use cases came up.

Example 4: The Right Fit — Spec & Submittal Review

A project team was overwhelmed with submittal and spec review volume. Several AI tools claimed to solve the problem, but the team had no way to separate genuine capability from marketing. They didn't know what to look for, what questions to ask vendors, or whether the pricing made sense for their project volume. We matched them to a tool we had tested directly for this exact use case — one we knew worked for their project type — and facilitated onboarding with access and pricing they wouldn't have gotten going in cold.

The Situation

The Value

The firm bypassed months of vendor evaluation. They landed on a tool that fit their workflow with pricing that made the ROI immediate. We stayed involved through the first month to make sure the workflow was set up correctly and the team was getting real value.

Example 5: Embedded AI Advisory for a Growing GC

A mid-size GC was scaling quickly but had no internal AI capability. Leadership knew AI tools were becoming standard in preconstruction but didn't know where to start, which tools were legitimate, or how to build a team that could actually use them. We embedded as an ongoing advisor — attending preconstruction meetings, identifying workflow gaps as they came up, recommending tools by task, running training sessions with the team, and acting as the point of contact between the firm and AI vendors. No guesswork, no wasted pilots.

The Situation

The Value

The firm built a functioning AI approach without hiring a dedicated tech role. The team developed genuine capability to evaluate tools themselves — knowing what questions to ask, what to expect from vendors, and how to integrate new tools without disrupting existing workflows. What started as advisory became the infrastructure for how they operate.