Adopting AI takes structure.Your people do the work.We provide infrastructure and direction.
What we provide
AI tools to help you standardize AI adoption across the entire enterprise in a controlled, consistent, and safe manner.
Our proprietary infrastructure, creating a consistent communication and orchestration layer across the entire organization, based on a multi-layered organizational chart representing your company.
Our proprietary tool providing a standardized methodology for identifying the workflows specific to your company’s reporting responsibilities, and AI processing that generates the detailed workflows within the organization.
Our proprietary AI operating standards — one centrally managed workspace that governs how AI processes workloads across every project.
Coaching and direction for your AI champions.
Guidance on where AI fits and where it doesn’t, department by department.
What you provide
One person leading AI adoption across the company, or champions within specific departments.
Foundation
Standards, protocols, controls
Champions
Your people take the lead
First workflows
Where AI pays off first
Expand
Department by department
Control
Company-wide governance of AI
Foundation first, then results. The same approach we took building enterprise systems inside the Viewpoint database.
AI Safety First — partitioned access to the production database
AI works in isolation. AI runs on its own dedicated machine, separate from your production systems — both the AI processing and the enterprise SQL database that holds its output sit on that machine. It reads from your production database. It never writes to it. When AI output needs to reach your systems, your production system pulls it in through a controlled step. Nothing is pushed from the AI machine.
AI reads your data. It never writes to production directly.
Enterprise AI workflow structure
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Standard workflow development
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AI Operating Standards — the guardrail layer for your AI
One centrally managed workspace that governs how AI processes workloads — across every project.
A central library tracks the status of every workspace and holds an inventory of all harness elements — protocol skills, plugins and hooks.
Automated checks block unapproved changes, wrong dates and overwritten files, so safety doesn’t depend on the AI remembering.
Work is scoped and approved up front; nothing runs without an explicit go-ahead.
The AI checks facts against sources, labels what it can’t confirm, and proves work is done before reporting it.
How work is divided, handed off and checkpointed across agent teams — keeping context windows from saturating mid-task and holding autonomous execution inside defined limits.
Decisions, status and open items carry forward from one session to the next.
Global project instructions deploy automatically to every workspace, so a change at the center reaches all of them with no manual update.
Design changes and unattended runs are checked by a separate AI reviewer before they ship.
Status written for people; technical detail kept in an appendix.
We’re committed to AI in construction, and we’re still mapping where it goes. We’d rather say so than pretend otherwise.
Have an AI champion on your staff, or ready to name one? Let’s talk.
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