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Industry

AI in Construction

Submittals, specs and field records, searchable across every project you have run.

Construction generates enormous document volume per project and throws almost all of it away at closeout. Drawings, specifications, submittals, RFIs, daily reports and change orders contain the answer to most questions that get asked on the next job, and none of it is searchable. Senteras builds the retrieval and processing layer over that history.

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What makes this hard

  • Specifications run to thousands of pages and compliance checking against them is manual, so misses surface as rework
  • Submittal and RFI turnaround is a schedule driver and almost entirely administrative
  • Estimating depends on institutional memory that walks out when a senior estimator retires
  • Field documentation is created on phones and never becomes queryable, so the same dispute gets relitigated without evidence

Where AI earns its place

Specification Compliance Checking

Check submittals against the specification section they answer and flag deviations before they go to the architect, rather than after rejection.

Fewer rejection cycles per submittal

Submittal and RFI Processing

Classify, route and draft responses to the routine portion of submittal and RFI traffic, escalating anything with schedule or cost impact.

Days off turnaround

Historical Estimating Support

Surface comparable scope and actual cost from completed projects when pricing new work, so estimates rest on your own history rather than recollection.

Comparable actuals on every bid

Field Documentation Retrieval

Make daily reports, photos and correspondence searchable in natural language, which matters most when a claim arrives eighteen months later.

Evidence located in minutes

Figures are drawn from Senteras engagements and are illustrative of typical results. Outcomes vary by data quality, infrastructure and scope.

The rules that shape the build

These are the constraints that decide the architecture, usually before anyone has picked a model. This is general information about the regulatory landscape, not legal advice on your obligations.

Contract notice provisions

Change and delay claims usually carry short notice windows. AI that surfaces a triggering event late is worse than no AI, so retrieval freshness matters more than model quality here.

Prevailing wage and certified payroll

Automated payroll review has to be auditable, because the penalty regime assumes a human verified it.

OSHA recordkeeping

Incident classification remains a human determination. The model can assemble the record, not decide the classification.

How we approach it

Built on your closed projects, not a generic corpus

The value in construction AI is almost entirely in the contractor's own project history, because means, methods and subcontractor performance do not generalise between firms. Senteras builds the retrieval layer over your closed jobs first and only then considers whether any model tuning is warranted. In most cases it is not, which keeps the cost down.

Where this applies

The same core systems, with the differences that matter in each setting.

General contractors
Submittal and RFI processing carry the clearest schedule payback.
Specialty and trade contractors
Estimating support against historical actuals matters more than document processing.
Homebuilders
Warranty and punch list triage across a large volume of similar units.
Architecture and engineering firms
Specification production and code compliance checking against drawing sets.
Facilities management
Work order triage and asset history retrieval after handover.

Common questions

Can AI check submittals against the specification?

Yes, and it is one of the clearest wins in the sector because the check is tedious, rule-bound and currently done inconsistently. It flags deviations for review rather than approving anything.

Our project history is scanned PDFs and photos.

That is the normal starting position and it is exactly what makes the retrieval layer valuable. The work is in ingestion and indexing rather than in the model, which is also why the cost is more predictable than people expect.

How does this help with claims?

A searchable record of daily reports, photos and correspondence is decisive when a claim arrives eighteen months later. Most contractors have the evidence and cannot find it inside the notice window, which is functionally the same as not having it.

Will it estimate for us?

It surfaces comparable scope and actual cost from your completed projects so an estimator prices against evidence rather than recollection. The estimator still estimates, because means and methods do not generalise between firms.

How we build it

Local & On-Prem LLM Deployment

The most powerful AI models, running entirely on your hardware.

Custom AI Agents & Automation

AI that doesn't just answer questions. It gets things done.

AI Strategy & Roadmap

A clear path from where you are to where AI can take you.

Document Processing

Extraction, classification and validation across formats you do not control.

Internal Knowledge Base

Answers from your own documents, under your existing permissions.

Contract Review

Flags deviations from your playbook, not from a generic standard.

Find out what this looks like for your organisation

A 30-minute call. We will tell you plainly whether AI is the right tool for the problem you have, including when it is not.

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