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HomeSolutionsKnowledge Systems & RAG for Construction
Knowledge Systems & RAG × Construction

Knowledge Systems & RAG for Construction & Contractors

Answers from your own documents — cited, access-controlled, and never made up. Shaped by the real problems in construction & contractors.

In one line

A RAG knowledge system for construction & contractors answers questions from your own documents — supporting work like bid & spec-book intelligence — by retrieving the relevant passages first and citing them, so answers come from your knowledge rather than a model's guesswork.
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Last updated June 2026
The fit

Knowledge Systems & RAG, shaped for Construction & Contractors

In construction & contractors, the answer usually exists — in a document, a policy, a past file, someone's head — but finding it takes time and the right person. 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. A knowledge system lets people just ask, and get an answer grounded in your real material.

For your sector the questions worth answering this way cluster around your documents and records — bid & spec-book intelligence and site-photo progress & safety monitoring. The system retrieves the relevant passages from your own sources, generates an answer grounded in them, and shows the citation, so every answer can be checked back to where it came from.

Two things make it trustworthy: it honors your access controls, so people only get answers from what they're allowed to see, and it says 'I don't have that' when your documents don't cover it instead of inventing a plausible reply. It runs on your infrastructure — your documents are never used to train someone else's model.

More on Knowledge Systems & RAGMore on AI for Construction
What we build

What people can just ask in 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

  • Construction answers live buried in documents, systems, and people's heads
  • Staff or clients wait on someone to look things up
  • You need answers that cite a trustworthy source, not a black box
  • You want a private assistant that never leaks your documents to train another model

What you get

  • A private assistant answering construction & contractors questions from your documents, with citations
  • Access controls so each user only gets answers from what they're allowed to see
  • Honest 'I don't have that' behavior instead of confident invented answers
  • Connection to your real sources — drives, wikis, ticketing, case files, databases
  • Deployed on your infrastructure and owned by you — your construction data stays yours

However we build it, you own it

Source code handed over, in full
Deployed on your infrastructure
Full documentation & handoff
Built to run without us
Questions

Knowledge Systems & RAG for Construction — answered

A general chatbot answers from the public internet and will confidently make things up about your construction & contractors work. A RAG system answers only from your documents, cites where each answer came from, and says 'I don't have that' when your material doesn't cover it. It's your knowledge, grounded and private — not a model's best guess.

Every answer is grounded in retrieved passages from your documents and shown with its citation, so an answer without a source is visibly one. When retrieval finds nothing relevant in your construction material, the system says it doesn't know rather than inventing a reply. It's constrained by design, not by hoping the model behaves.

It honors your existing access controls, so a user only gets answers drawn from construction & contractors documents they're permitted to see. Everything runs on your infrastructure, on-premise or in your cloud account, and your documents are used to answer your questions — never to train a shared or third-party model.

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.

Knowledge Systems & RAG 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.

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