Forecasting & Machine Learning for Construction & Contractors
Know what you'll sell, staff, and stock next month — and order against it. Shaped by the real problems in construction & contractors.
In one line
Forecasting & Machine Learning, shaped for Construction & Contractors
Plenty of construction & contractors decisions still get made on gut feel and last year's spreadsheet — how much to stock, whom to staff, what to set aside for risk. Bids get priced against spec books no one had time to read end to end, so scope gaps and addenda changes surface after the contract is signed. RFIs, submittals, and change orders sit in inboxes while the schedule slips and the money question stays open. Meanwhile subcontractor COIs lapse, pay-apps and lien waivers pile up, and the daily reports that protect you in a dispute get written from memory. Your own history holds a better answer than instinct, if something turns it into a forward view.
For your sector the models that pay off predict the things you plan around — bid & spec-book intelligence and site-photo progress & safety monitoring. We build them on your actual data and pick the technique on merit: often a well-chosen statistical model beats a neural network on limited data, and we say so honestly rather than reaching for the most impressive-sounding tool.
We validate every model against data it hasn't seen and tell you plainly where it's reliable and where it isn't — a forecast with honest error bars beats a single confident number. The models, code, and documentation are yours to run and retrain, on your infrastructure, with no per-prediction fee.
What we predict for construction
Bids get priced against spec books no one had time to read end to end, so scope gaps and addenda changes surface after the contract is signed. RFIs, submittals, and change orders sit in inboxes while the schedule slips and the money question stays open. Meanwhile subcontractor COIs lapse, pay-apps and lien waivers pile up, and the daily reports that protect you in a dispute get written from memory.
Bid & spec-book intelligence
parse spec books and drawings to surface scope gaps and addenda changes before you price the job
Site-photo progress & safety monitoring
computer vision over the photos your crews already take, flagging progress and potential hazards for a human to review
RFI, submittal & change-order chase
automate the paperwork loop between GC, subs, and architect that stalls jobs
Subcontractor COI & compliance tracking
watch insurance certificates and expirations so no trade works uncovered
Pay-app & lien-waiver processing
read and reconcile applications for payment and waivers against the schedule of values
Daily-report & schedule-risk intelligence
generate daily reports from field data and flag jobs trending toward slippage
This is for you if
- You plan construction stock, staffing, or cash on gut feel
- You want to know which customers churn, or which cases carry risk
- You need to spot fraud, failures, or problems before they cost you
- You have years of data but nothing turning it into a forward view
What you get
- A forecasting or scoring model built on your construction & contractors history, validated honestly
- The right technique for bid & spec-book intelligence — classical ML or deep learning, chosen on merit
- Clear accuracy expectations, including where the model is and isn't reliable
- Integration so predictions reach the people and systems that act on them
- The models, code, and documentation handed over — yours to run and retrain
However we build it, you own it
Forecasting & Machine Learning for Construction — answered
Less than most people assume — a couple of years of ordinary construction & contractors history is often enough, and some scoring problems need surprisingly little. Before we commit, we look at your data and tell you honestly what it can support, rather than building something that looks confident and isn't.
No — and anyone who says so is selling something. For a lot of construction & contractors forecasting, a well-chosen statistical model beats a deep network: more accurate on limited data, cheaper to run, easier to trust. We pick the technique that performs best on your problem, not the one that sounds most advanced.
We validate against data the model hasn't seen and tell you plainly how accurate it is and where it's weak. You'll know when to lean on the forecast and when to apply your own construction judgment — which beats a single confident number that hides its uncertainty.
Yes — connecting to your project-management and document tools is part of the build, whether that's Procore, an Autodesk product, Sage, or a shared drive full of PDFs. The point is a system that reads and writes where your team already works, so RFIs, submittals, and daily reports flow through your existing process rather than becoming another login no one opens.
No. It runs computer vision over the photos your crews already take and flags potential hazards — missing PPE, unguarded edges, blocked egress — for a human to review. It never guarantees a site is safe or compliant; it just surfaces things worth a second look so your people see more than one walk a day can catch.
Forecasting & Machine Learning for Construction. Let's scope it.
A short call, then a clear, agreed scope in writing. No obligation, and an honest no if it isn't a fit.