Private AI for contractors.

Contractors generate an enormous amount of document work for businesses their size: bids and estimates, RFIs, submittals, plansets and specifications, change orders, contracts, and lien paperwork — usually managed by a small office, often with no dedicated IT staff, and scattered across email, shared drives, and phones. AI is genuinely useful against that pile. The catch is that a lot of it is confidential: client drawings, bid numbers, contract terms. Putting that into a public chatbot sends it somewhere you don't control. Private AI lets you use it on your own hardware, where the data stays.

Where AI earns its keep on a job

• Spec and planset Q&A — "what does Section 07 say about flashing?" answered from the actual project documents, not a guess.
• Bid and estimate assembly — analyzing solicitation documents, drafting scope narratives, scoping subs.
• RFI drafting — turning a field question into a clean, complete RFI in minutes.
• Change orders and claims — assembling backup and drafting the narrative.
• Jobsite notes — turning a pile of site photos and voice memos into structured daily logs.
• Contract review — surfacing the clause that matters before you sign it.

Why "private" matters more for contractors than people expect

Contractors increasingly carry data-handling obligations they didn't a few years ago. None of these require private AI, but they all point the same direction — keep confidential project data inside your control:

• Government and defense work comes with strings. Contractors that handle Controlled Unclassified Information on defense projects must meet the security controls in NIST SP 800-171 — and any cloud they use has to meet a FedRAMP-equivalent bar that ordinary commercial AI services don't clear. The CMMC certification program that verifies this began phasing into contracts in 2024–2025. (This one is defense-specific — it doesn't apply to every public-works job — but it shows where the bar is heading.)
• "Don't train your AI on our data" is becoming standard contract language. A 2025 federal directive now pushes agencies to bar vendors from using non-public government data to train commercial AI without consent, and proposed federal clauses go further still. In private work, confidentiality agreements increasingly include the same restriction — language barring you from putting confidential information into third-party AI systems. These clauses are spreading fast; running AI in-house keeps you on the right side of them by default.
• Your cyber insurance has expectations. Cyber-liability underwriters no longer just take your word for it — they require concrete controls (access management, encryption, knowing where your data goes) before they'll bind a policy, and misrepresenting your practices can void a claim. Some carriers are beginning to add AI-specific exclusions. Where your data is processed is squarely part of that picture.

The pattern across all of it is the same: these obligations rarely say "no AI." They say where data may live, who may touch it, and that it must not be fed to outside systems. Public-cloud AI puts you on the wrong side of that by default. In-house inference keeps the data where those clauses assume it stays.

The part most contractors miss: you can bill AI to the job

Here's the angle that turns AI from a cost into a line item. Contractors already pass direct costs through to owners — that's what cost-plus, GMP, and T&M contracts are built to do. AI used on a specific project is a direct project cost, the same as the BIM license or the reproduction fee. The only thing missing has been a way to attribute AI usage to the right job at the moment it's used.

That's what makes the Interchange AI Gateway the centerpiece for a contractor: it logs every AI interaction by user and project, so the spend lands in the right cost code instead of disappearing into overhead. For the full accounting mechanics — which contracts make this seamless and which require pricing it into the bid — see AI as a project cost code and the cost recovery overview.

Where to start

If you want to try this with zero setup, Archivist runs private AI on a single Windows machine — point it at a project's specs and start asking questions, with nothing leaving the laptop. When you're ready to serve a crew and bill usage back to jobs, that's the Interchange and inference server conversation. You can also see what we do for construction firms specifically.