AI for construction estimating and bid handoffs

If you run precon, you already know the estimate is not the bottleneck. The handoff is. This site is a plain directory for that problem.

What this is for

Name the real leak: estimate to ops dies in email, exports, and tribal memory.
Skip the science project. Another dashboard is not a workflow.
Build one owned path: historical costs in play, package that survives award, field lessons that come back.
Use the guides below when you need a concrete next step, not a pitch deck.

Guides

Bid handoff checklist: what has to survive from estimate to ops The short list of what cannot get lost between win and kickoff.
Why your estimating API returns the customer record, not the estimate Coming next. Integration theater vs the data that actually prices the job.
Historical cost data: how to make last year’s jobs useful for this bid Queued.
Takeoff vs pricing: where AI helps first (and where it shouldn’t) Queued.
WinEst, Edge, and “we’ll export it somehow”: living with imperfect tools Queued.
Preconstruction meeting brief: what the estimator actually needs in the room Queued.
Risk flags before award: reading the bid package like an operator Queued.
Field-to-estimate loop: capturing what the job taught you Queued.
Hiring an estimating coordinator vs teaching the team to think in AI Queued.
One-day Kickstart for estimating teams: what “done” looks like Queued.

Chief AI Officer runs a one-day Kickstart with your estimating and ops leads. No science project. One owned workflow you can run Monday.