Field notes / our own floor

Before, after,
and what it cost us.

No client logos, no invented case studies. This is what our own operation looked like before we started and what it looks like now — including the parts that took two tries.

5th
Generation manufacturer
Daily
AI running our own operation
30d
To first live workflow
0
Unapproved writes to your ERP
Intake

The interrupt tax

Before

Every question — where is the file, who approved this, what is the process — landed on two or three people. Their real work happened after hours.

After

One AI front desk answers the repeat questions, pulls the file, and only escalates what genuinely needs a human. The interruptions stopped being a job.

Cycle

3 wks

Uploads

Marketplace and ERP prep

Before

Product data was cleaned by hand into templates, one tab at a time, and rejected uploads were found the next morning.

After

Cleanup and template fill run automatically, then park in a review queue with a diff. A person approves; nothing writes on its own.

Cycle

5 wks

SOPs

The binder nobody opened

Before

Procedures lived in a printed binder that went stale the week it was printed, plus whatever the shift lead remembered.

After

Floor teams ask task-specific questions and get the current step. Employees submit updates by photo; owners approve the official version.

Cycle

6 wks

Product dev

Ideas that died of ambiguity

Before

New product ideas sat in email threads until somebody had a free week to build a comparison nobody trusted.

After

Rough ideas turn into comparison tables, cost math, and a launch plan in a day — so the go / no-go actually gets made.

Cycle

4 wks

Visibility

Work nobody could count

Before

Half the operation ran out of inboxes. No volume, no aging, no owner — so it could never be staffed or prioritized.

After

Live queues and dashboards put a number on the invisible work. The first week of data changed two hiring decisions.

Cycle

2 wks

The misses

What did not work

Before

We tried to automate quoting judgment end-to-end. The model was confident and wrong in the expensive direction.

After

We pulled it back to assist-only: AI assembles the inputs, the estimator still decides. That honesty is why the rest gets used.

Cycle

Ongoing

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