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.
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.
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.
~14 hrs/wk
Interruptions pulled off two people
Cycle 3 wks
Product data was cleaned by hand into templates, one tab at a time, and rejected uploads were found the next morning.
Cleanup and template fill run automatically, then park in a review queue with a diff. A person approves; nothing writes on its own.
~9 hrs/wk
Manual template prep removed
Cycle 5 wks
Procedures lived in a printed binder that went stale the week it was printed, plus whatever the shift lead remembered.
Floor teams ask task-specific questions and get the current step. Employees submit updates by photo; owners approve the official version.
1 day
New-hire ramp on a procedure, from ~1 week
Cycle 6 wks
New product ideas sat in email threads until somebody had a free week to build a comparison nobody trusted.
Rough ideas turn into comparison tables, cost math, and a launch plan in a day — so the go / no-go actually gets made.
2 days
Idea to go / no-go, from ~3 weeks
Cycle 4 wks
Half the operation ran out of inboxes. No volume, no aging, no owner — so it could never be staffed or prioritized.
Live queues and dashboards put a number on the invisible work. The first week of data changed two hiring decisions.
100%
Of queue work now counted and owned
Cycle 2 wks
We tried to automate quoting judgment end-to-end. The model was confident and wrong in the expensive direction.
We pulled it back to assist-only: AI assembles the inputs, the estimator still decides. That honesty is why the rest gets used.
~30%
Of the quoting build reverted to assist-only
Cycle Ongoing