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Case Studies / Manufacturing
CASE STUDYMANUFACTURING90-DAY ENGAGEMENT

From tribal knowledge to an AI operating system, in 90 days.

How a private manufacturing group went from idea to a working AI foundation: four AI employees conversing in Microsoft Teams, a searchable company memory, and a defensible path to one-third more enterprise value.

4
AI employees hired: named, role-based, managed
3
core systems verified live in production
90
days from kickoff to working foundation
1.33×
base-case enterprise value path (appraisal math)
THE CHALLENGE

The business ran on knowledge locked in people's heads

A private manufacturing group with one goal: reduce the cost of operating the business. Estimating, quoting, reporting and file search all depended on manual effort and tribal knowledge, and on the owner personally. That meant high cost to serve, high key-person risk, and a harder story to tell in any future diligence.

The bet: AI becomes valuable when it's connected to company memory, approved tools and human approval gates, not when it's a chat window. So we didn't deploy a chatbot. We built an operating system.

THE APPROACH

Learn the work. Prove the value. Then build.

Infrastructure was only built for patterns that proved useful first. No speculative technology spend.

APRIL · DISCOVERY
Learn the work
Mapped the workflows, knowledge sources and risk boundaries where AI could remove the most cost.
“What work should AI support?”
MAY · PROOF OF CONCEPT
Prove the value
Tested AI teammates in Teams and email: estimating support, file intake and report generation.
“Which patterns earn hardening?”
JUNE–JULY · BUILD
Build the foundation
The durable root system: memory, knowledge map, profiles, tool connectors and observability.
“What makes AI repeatable?”
WHAT WE BUILT

An operating system, not a chatbot

Above the line: four AI employees people actually talk to. Below it: the six-layer root system that makes them dependable: the real asset.

THE SURFACE · WHAT PEOPLE SEE
A
Abby
CHIEF OF STAFF · MANAGER
Assigns work, tracks evidence, reports up.
V
Val
ESTIMATOR
Turns RFQs and job history into estimate drafts and clarifying questions.
J
Jacob
SCOPE REVIEWER
Red-teams every quote: scope gaps, risks and missing details before approval.
L
Lucy
COMMUNICATIONS
Turns technical progress into client-ready reports, emails and updates.
THE ROOT SYSTEM · WHAT MAKES THEM WORK
01
Company memory
Meaning-based search finds concepts, not just filenames.
02
Knowledge map
Connects people, projects, systems and decisions.
03
File intake
SharePoint and file drives flow into AI-usable context.
04
Employee profiles
Role-specific instructions, tools, boundaries and handoffs.
05
Tool connectors
Teams, email, Odoo, reporting. Approved access only.
06
Observability
Every AI action traced, scored and reviewable.

Human oversight throughout: specialists execute and escalate uncertainty; final decisions stay with people. Anything sensitive or external requires owner approval.

PROOF IT WORKS

Already working in real channels

ABBY · MICROSOFT TEAMS
Abby, what's blocking this week?
Two items: the Westfield quote needs a material spec, and Val is waiting on the RFQ drawings. I've flagged both owners.
AI employees answer where people already work. No new app to learn.
VAL · RFQ REVIEW
✓Material spec confirmed
✓Quantities match drawings
✓Similar prior job found
!Finish spec missing: ask customer
3 OF 4 ESTIMATING INPUTS READY
RFQ review, assumptions and missing-input checklists drafted in minutes.
LUCY · WEEKLY REPORT
Operations update · Week 12SENT
Drafted from company files
Company files become polished, client-ready reports and updates.

Stylized recreations of proof-of-concept sessions from the May pilot phase.

CURRENT STATE

An honest status board

Three systems verified live in production; two in structured review. Engineering discipline, not spin. This transparency is part of how we work.

AI communication channels
All four AI employees responding on their Teams paths
LIVE
Meaning-based company memory
Search engine verified in production, v1.18
LIVE
Conversation continuity
AI employees remember context across sessions
LIVE
Business system connectors (Odoo/ERP)
Built and connected; completing stability review before rollout
HARDENING
Self-improvement scaffolding
Foundation in place; becomes the improvement engine next phase
PILOT
WHAT IT IS WORTH

A defensible path to one-third more enterprise value

Two drivers: EBITDA uplift (faster estimating, search and reporting; less rework) and multiple expansion (lower key-person risk, documented process, cleaner diligence). Enterprise value = adjusted EBITDA × market multiple, baseline 3.75× for small private manufacturing.

1.12×
Conservative
+5% EBITDA · 4.00× multiple
1.33×
Base case
+15% EBITDA · 4.35× multiple
1.65×
Proven ROI
+30% EBITDA · 4.75× multiple

Scenario model grounded in standard appraisal practice, built to survive buyer diligence. Day-180 target: every claim backed by a measured number: hours saved, quotes accelerated, rework avoided.

SERVICES USED

This engagement, as catalog services

Knowledge foundation buildCustom agentic harnessGateway integrationsVirtual AI employee pilot
“
The first 90 days built the root system. The next 90 turn it into measured business results.
90-DAY PROGRESS REPORT TO STAKEHOLDERS

Your business could have its own AI OS in 90 days.

Same playbook: learn the work, prove the value, build only what earns it.

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