AI Recommendation Engine

Join is project management for the people who build actual buildings. As Head of Design, I lead a small team and ship product across the platform.

Ideas is an AI recommendation engine that surfaces cost-saving material alternatives inside construction estimates. A less experienced estimator might spec a finish at full cost when a substitute would do the same job for half, and that knowledge gap compounds across every line item in every project. Ideas surfaces those substitutions automatically.

The original plan was a materials marketplace. Customer interviews moved us off that direction — estimators didn’t know what alternatives existed, so they wouldn’t browse a catalog on their own. I took on both design and an acting PM role, pivoted the concept to a recommendation engine, and we shipped in two months.

Suggestion carousels

AI-generated suggestions appear as contextual carousels ranked by cost-saving potential. Each carousel groups alternatives by where they appear in the estimate and by construction phase, so estimators see relevant options without searching.

Human review layer

These suggestions affect real buildings and real budgets, so a materials researcher validates every suggestion before it reaches an estimator. The model is advisory, not authoritative.

We used AI-coded prototypes to test card density with real estimate data before engineering built anything. Each card shows UniFormat and MasterFormat classification codes — estimators told us in interviews these were non-negotiable for trust.

Forced comparison

Every recommendation has to be weighed against alternatives before an estimator can accept it. Suggestions are surfaced by the model, but the decision sits with the estimator and nothing gets auto-applied.

Results

One enterprise customer saved $500K on their first project estimate within 30 days of launch. Decision-making time dropped 50% across the product.

"Join secures growth investment from construction giants DPR Construction and STO Building Group."