Signals built for industry
Submittal turnaround, quote revision velocity, estimator load, historical award rate by general contractor, consumption drift, and margin distance from your win band.
Atlas AI
The next best action, with the evidence behind it
Probability scores describe a deal. Atlas AI decides what to do about it — and shows the records that justify the call, so pipeline reviews debate substance instead of intuition.
Atlas action queue — sample data
Revise quote 4 — pricing 9% above win band
Harborline Energy — Unit 3 retrofit
$412K open
Call estimator: submittal 6 days past norm
Ridgeway Constructors — Phase II
+18% award lift
Open renewal conversation 90 days early
Cascade Foods — service agreement
$96K recurring
Reorder drift detected on two SKUs
Fulton Branch — MRO account
Retention risk
How it works
Decisioning designed for long award cycles
Models tuned per business unit
Atlas AI trains on your own closed-won and closed-lost history, so a fabrication division and a service division get different recommendations.
One action, not a dashboard
Each rep, estimator, and branch manager opens a ranked queue. The recommendation states the action, the account, the reason, and the expected impact.
Explainable and governed
Every score links to the records that produced it, retains full history, and respects role-scoped visibility. Admins control which data each model may read.
Related
Keep exploring
More direction. Stronger relationships.
Watch Atlas AI rank your own pipeline
Bring a slice of historical award data. We show scoring, evidence, and the action queue your team would see on day one.