Specs, standards & submittals
Check vendor data and design documents against the requirements, with every finding linked to the page it came from.
Submittal review, requirements traceability, and standards checks.
AI systems that handle the standards review, document checks, and formatting, so your engineers can design the system and run the calculations. Connected to your data and tools, built around how your team works.
01 / WHAT WE BUILD
Purpose-built systems for specific bottlenecks, not another tool your team has to work around.
Check vendor data and design documents against the requirements, with every finding linked to the page it came from.
Submittal review, requirements traceability, and standards checks.
Turn test data and calculation inputs into draft reports and summaries, with assumptions stated and sources cited.
Test-result summaries, calculation package drafts, and recurring status reports.
Compare revisions, check drawings against a checklist, and trace what a change touches before it reaches review.
Revision comparison, drawing checks, and change-impact tracking.
ONE EXAMPLE / SUBMITTAL REVIEW
Submittal review is one example: compare a vendor datasheet against the specification, with both sources cited on every line. Visible evidence, clear limits, and human control guide every system we build.
Illustrative example. Select an item to compare the specification with the submittal.
SPEC / SECTION 23 21 23 · PAGE 5
“Motors shall be 460 V, three-phase, 60 Hz.”
SUBMITTAL / PUMP DATASHEET · PAGE 3
Motor: 208 V, three-phase, 60 Hz.
Voltage does not match the specification. Mark for resubmittal, or confirm the available electrical service before accepting an alternate.
02 / HOW WE WORK
A small, focused start. Clear boundaries. A working system, not a slide deck.
Walk through the real process, inspect representative inputs, and identify where automation could earn its keep.
One workflow, defined inputs, and agreed success criteria. Test quality and usefulness with the people doing the work.
Connect the necessary systems, establish access controls, and plan monitoring, handover, and ongoing support.
03 / WHO’S BUILDING

I’m Ryan Gallagher. I spent five years as a mechanical engineer designing systems for U.S. Navy ships. I know the drawings, specifications, vendor submittals, and review cycles because I worked in them every day.
That’s where I started applying AI to engineering work. Today I build production AI systems end to end, from understanding the workflow to deployment.
A FEW PRACTICAL QUESTIONS
Not necessarily. The starting point is your current workflow and systems. Any pilot will define the integrations it needs rather than assume a full technology overhaul.
That possibility is part of the design. We agree on evaluation criteria, keep source evidence where relevant, and add human review at consequential decision points. The system’s limits should be visible, not hidden.
We agree on data access, model providers, retention, and deployment requirements before using client data. Don’t send sensitive or confidential documents in an initial inquiry.
A walkthrough of the task, who does it, how frequently it happens, and what makes it difficult. No need for a polished brief. Just a concrete example of the workflow.
LET’S START WITH ONE WORKFLOW
Tell me what the task is, who handles it, and where the time goes. We’ll see whether there’s a practical way to improve it.