Door 04 of 04

AI Engineering & Governance

AI that does real work inside the institution, scoped, governed, and defensible in front of an examiner.

Real work. No new audit findings.

Sound familiar?

  • Leadership wants "AI" and nobody can say what it should do on Monday morning
  • Staff are already pasting customer data into public chatbots with no policy, no DLP, and no log
  • A Copilot rollout stalled because nobody scoped what it can see in SharePoint
  • Reports assembled by hand every week from the same three systems
  • The examiner asked for your AI policy and you do not have one they will accept

What we do

  • Report pipelines that gather, reconcile, and format, with a human review step kept where it matters
  • Document and ticket automation inside M365, SharePoint, and your line-of-business systems
  • M365 Copilot scoped correctly, permissions cleaned up before it is turned on
  • DLP so PII never leaves for an AI service
  • An AI policy regulators have already seen and accepted
  • Custom agents and detection models, built for your data

Relevant build

Proof it's been done before.

Built from nothing · Product / Software / AI

LakeMonster.com

A lake-data platform and fishing app built end to end: web platform, mobile app, AI-driven fishing intelligence, multi-site lake cameras with AI detection, live streaming, and a subscription business on top. Proof that ERB One designs, engineers, and ships complete products: software, hardware, and cloud together.

Every block placed by hand.
GoAICamerasCloud

The report that ate a workday

Problem
A recurring report was assembled by hand from several systems, every time, taking hours of a skilled person's week.
What we found
Every step was repeatable. The work was gathering, reconciling, and formatting, which is exactly what an automated AI pipeline is good at.
Result
An automated report pipeline that replaced hours of manual work, with a human review step kept where it matters.

All builds and case blocks →

Behind door 04?

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