// industries · aviation mro
Turn reactive maintenance into predictive intelligence.
Most aviation MROs run blind until equipment fails. We wire shop-floor telemetry into the legacy ERPs that actually run your operation — so TAT commitments are something you can see, not something you hope for.
> ask_ai("which work orders are at risk of blowing TAT?")
x ERROR: source of record = legacy_erp.dbf
x no API. no telemetry. no audit trail.
> deploy mro_modernization_stack
+ shop-floor telemetry → staging
+ legacy ERP exposed read-only
+ TAT risk visible per work order
// the operating reality
Your shop already produces the data. It just can't reach it.
Every job traveler, inspection sign-off, and parts issue is recorded somewhere — an ERP from another decade, an Access database one retirement away from orphaned, a spreadsheet only the lead knows how to read. The failures aren't surprises. The data that predicted them was just locked up.
What unplanned equipment failure costs a mid-size MRO every year it keeps running reactive.
The AI-Ready Data Audit turns a preliminary blueprint into a validated engineering plan, for $5,000.
Work trusted by the US Navy and US Air Force happens onshore, end to end.
// the mro modernization stack
From shop floor to system of record
We map every system of record — ERP, MES, maintenance logs, the FoxPro database nobody admits to — and find where the data actually lives, who owns it, and what is reachable.
Decades-old ERPs untangled and exposed through governed, read-only access layers. No rip-and-replace, no big-bang migration, no downtime on the floor.
Shop-floor telemetry wired into the systems that run your operation, so equipment status is data in a queryable table — not a walk to the floor.
Dashboards and AI agents that answer real questions: which jobs are at risk, which parts keep causing delays, where TAT is slipping — with an audit trail on every query.
// what you could ask
Questions your systems should be answering
// governed by design
CMMC, ITAR, CUI — AI doesn't get a pass.
If you supply aerospace and defense programs, "just upload it to the cloud" is not an architecture. We build least-privilege, read-only access layers that keep controlled data inside the boundary you already defend — with an audit trail on every query an AI agent runs.
> grant ai_agent SELECT on work_orders
+ scope: read-only · least privilege
+ boundary: restricted programs excluded
+ audit: every query logged
> export work_orders → public_cloud
x denied by policy
// tools we bring
Built for the shop floor
// faq
Aviation MRO — straight answers
Can AI access our MRO data without violating CMMC or ITAR?
Yes. We build least-privilege, read-only access layers that keep controlled data inside the boundary you already defend, exclude restricted programs, and log every query an AI agent runs. We are designed to support your compliance posture — we do not certify compliance.
Our shop runs on a legacy ERP with no API. Can you still connect it?
That is the core of what we do — extracting from decades-old ERPs, Access databases, and .dbf files and exposing them read-only, without disrupting the jobs that depend on them. No rip-and-replace, no downtime on the floor.
How does this help us hit TAT commitments?
We wire shop-floor telemetry into your systems of record so TAT risk is visible per work order — before the miss, not after. The failures were never surprises; the data that predicted them was just locked up.
What does it cost to start?
The preliminary AI Data Access Blueprint is free. The AI-Ready Data Audit is $5,000 for five days, credited back toward the build if you hire The Mad Botter.
// where to start
Map the access problem before buying another AI tool.
The AI Data Access Blueprint is a free preliminary map of where an AI initiative will stall in your shop: data access, legacy systems, governance, or ownership. The paid audit then validates it against your real systems.
We map the fix in 5 days for $5,000 — credited toward the build if you hire us.