Customertimes
Manufacturing AI Practice
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AI Agent Sprint ยท Two days ยท On site

Grow the plant.
Not the headcount.

A fixed-fee, two-day working sprint for mid-market manufacturers. Your team brings the manual work that eats their week โ€” we leave you a signed 90-day AI agent roadmap and a working prototype, built in your environment, on the platforms you already run.

Format
2 days
Fee
Fixed
Output
Signed roadmap
Built in the room
1 live agent
The backlog you already know about

Sound familiar?

Every line below is a pattern we see across mid-market manufacturing โ€” the numbers come from real plants, including a $1B manufacturer we ran this sprint with. If three or more read like yours, the sprint pays for itself in the first month.

LOG-01

Shipping paperwork โ€” load sheets, schedules, carrier docs โ€” assembled by hand every day from the ERP, spreadsheets, and a routing tool, against a hard afternoon cutoff.

30 min ร— 7/dayagent target: 5 min
SLS-02

Inventory and stock-availability reports take hours to build, so they're stale by the time sales quotes from them โ€” and the same unit gets sold twice.

4โ€“6 hrs/reportplus double-sold units
ENG-03

Estimates for custom and configure-to-order work are educated guesses dug out of old spreadsheets and senior engineers' heads โ€” so 20 units get scheduled and 16 get built.

30โ€“40% custom BOMsestimated by memory
EHS-04

Safety incidents live on paper: handwritten form, scan, re-key into Excel โ€” months from incident to closed corrective action.

30โ€“40 min/incidentup to 3 months end-to-end
ITS-05

A capable IT team spends its days on password resets and "how do I do this in the ERP" questions instead of projects.

546 tickets/mo179-ticket backlog
LGL-06

One or two legal staff carry the entire contract load โ€” first-pass reviews measured in days, on the other side's paper.

657 contracts/yr5โ€“7 hrs per MSA
How the sprint runs

Two days. Your people. Their pain points.

No slideware audit. You nominate one champion per function โ€” the people who actually do the work โ€” and we facilitate. The decisions are theirs, which is why the roadmap survives after we leave.

Day 1 โ€” Discover & ideate

Find where the hours go

  • Pre-work review: your team's own AI-readiness scores and pain inventory, collected before we arrive.
  • Process & data walk-through: map the manual work, the systems it touches, and where the data actually lives.
  • Use-case generation: typically 20+ candidate agents surfaced across functions.
  • Value-vs-effort scoring: every idea ranked on business impact and data readiness โ€” in the open, with your team holding the pens.
Day 2 โ€” Decide & build

Leave with a signed plan

  • Consolidation: the long list becomes a short portfolio of agents, each with a one-page business case and a measurable KPI.
  • Live build: we prototype the first agent in the room, in your environment, with your documents.
  • 90-day roadmap: quick wins first, sequenced by data readiness โ€” including what shouldn't be an AI project at all.
  • Executive sign-off: your champions present the portfolio to your leadership. They own it; we support it.
What you keep

The deliverables

Agent one-pagers

Each selected agent documented: the problem, the systems it touches, success criteria, KPIs, and effort size โ€” ready to hand to any builder, including your own team.

Value / effort matrix

The full scored inventory of every idea raised โ€” including the ones that didn't make the cut, and why.

90-day roadmap

Sequenced, owner-assigned, executive-signed. First agents live in month one, not quarter three.

Working prototype

The agent we build on Day 2 stays in your environment, with a step-by-step build runbook so your team can repeat the pattern.

Data readiness read

An honest assessment of which use cases your data supports today โ€” and what the gaps will cost you if left alone.

Platform recommendation

Microsoft, Anthropic, AWS, OpenAI, Google โ€” each use case matched to the right platform and model, with running costs. Never picked by default.

Field-proven

Built with a top-10 North American trailer manufacturer

A ~$1B, family-owned manufacturer facing a 43% market downturn โ€” while opening new plants and targeting 50% growth without proportional hiring. Ten functional champions, three days, one signed decision.

Raw ideas surfaced
23
Signed initiatives
9
First agents live
Month 1
Prototypes built in-room
2

"Drive the technology โ€” don't let the technology drive you."

Client leadership, Day 1 of the sprint
Why it works

Our ground rules

R-1

Augmentation, not replacement

The goal is your existing team handling more โ€” not fewer people. That's the only version of AI a stretched workforce will actually adopt.

R-2

Your stack, not ours

The agent's logic lives in your workflow, not in a vendor. We've built the same designs on Microsoft Copilot, Claude, AWS, and OpenAI โ€” so we start from what you already license and connect to the ERP and files you have. Nothing gets ripped out, and no platform locks you in.

R-3

Read-only until trust is earned

First agents observe, draft, and recommend under least-privilege access. Autonomy is increased only after measured performance โ€” your IT and legal teams will thank us.

R-4

We tell you when it's not AI

Some of your worst reporting pain is a data-plumbing fix, not an agent. We'll say so โ€” that honesty is why the roadmap holds up.

R-5

Your people own the result

Champions present the portfolio to their own executives and lead adoption in their functions. We facilitate, build, and train โ€” you keep the capability.

Fixed fee ยท No obligation beyond the sprint

Bring your worst spreadsheet.

A 30-minute scoping call is enough to tell whether the sprint fits your plant. If it doesn't, we'll tell you that too.

Book a scoping call