AI for manufacturers · Built from the work

Practical AI for the work between the machines.

Quoting, POs, quality records, shift handoffs, maintenance notes, supplier email, and the tribal knowledge your team depends on. We learn how the work moves, build the tool around it, train the people using it, and stay involved after launch.

Walk us through your operation See where AI fits ↓

Start with one workflow

Not an AI roadmap that takes a year. One working loop your team can test against the way the job is done today.

Keep your ERP. Keep human judgment. Fix one expensive handoff, queue, search problem, or follow-up cycle first.

01 · The operating gap

Manufacturing is automated. The coordination around it often is not.

Machines can hold a thousandth. The information around the job still moves through inboxes, clipboards, shared drives, spreadsheets, meetings, and memory. That is where practical AI can help first.

Documents

RFQs, drawings, specs, POs, forms, certificates

Messages

Supplier replies, customer questions, shift notes, approvals

Decisions

What is late, what changed, what needs review, who owns it

Follow-up

Dates, actions, evidence, escalations, and the next handoff

02 · Where AI fits

Start with the department carrying the manual load.

The best first project is usually easy to describe without using the words AI, agent, or transformation. It is a job the team already knows should work better.

01 · Function

Supply chain and purchasing

Buyers spend the day reading supplier email, updating dates, chasing acknowledgements, and explaining shortages.

Practical first builds

PO acknowledgement and promise-date tracker
Past-due follow-up drafts with buyer approval
Shortage briefing built from ERP, email, and open actions
Supplier performance summaries from actual correspondence

Where people stay in control

Your buyer still owns supplier relationships, expedites, and commercial decisions. The system keeps the facts and follow-up organized.

02 · Function

Quality

Inspection records, NCRs, corrective actions, customer complaints, and audit evidence live in different places.

Practical first builds

NCR intake that classifies issues and gathers missing information
Corrective-action tracker with owners, evidence, and due dates
Search across procedures, inspection history, and past defects
Audit pack assembly with source links and human sign-off

Where people stay in control

Quality approves every disposition, root cause, and regulated record. AI can prepare and connect the evidence, not make the final call.

03 · Function

Continuous improvement

Good ideas come out of walks and events, then disappear into notes, spreadsheets, and crowded action lists.

Practical first builds

Gemba note capture that turns observations into assigned actions
Daily loss summaries grouped by recurring cause
Kaizen follow-up that checks owners, dates, and evidence
Before-and-after briefing assembled from existing plant data

Where people stay in control

The CI leader decides what is causal, what is worth changing, and whether the result held. The tool keeps the improvement loop from going quiet.

04 · Function

Production and operations

Shift handoffs depend on whiteboards, radio calls, spreadsheets, and what the last supervisor remembered to mention.

Practical first builds

Shift-ready briefing from open orders, shortages, and downtime
Digital handoff that carries unresolved actions to the next shift
Production-status summaries written for each role
Exception alerts when a job, material, or approval stops moving

Where people stay in control

Supervisors still set priorities and respond to the floor. AI assembles the current picture and flags what needs attention.

05 · Function

Maintenance

Work requests arrive by radio, text, hallway conversation, and paper. History is incomplete when the same problem returns.

Practical first builds

Maintenance intake that structures operator descriptions
Repeat-failure search across work orders and technician notes
Parts, owner, and due-date follow-up for open repairs
Planned-maintenance briefings based on upcoming production needs

Where people stay in control

Technicians diagnose equipment and approve the work. The system improves intake, history, coordination, and preparation.

06 · Function

Sales, RFQ, and estimating

RFQs arrive with drawings, emails, revisions, and missing details. Estimators spend more time assembling the package than applying judgment.

Practical first builds

RFQ inbox that identifies customer, part, revision, and due date
Missing-information checklist and customer question draft
Search across similar jobs, assumptions, and prior quotes
Quote-status tracker from receipt through customer follow-up

Where people stay in control

Estimators own process, risk, margin, and final price. AI prepares the file and finds relevant history without pretending it knows the shop.

07 · Function

Engineering and document control

Engineers lose time finding the right revision, answering repeat questions, and moving information between drawings, specs, and systems.

Practical first builds

Controlled search across specifications and approved documents
Change-package summary with affected parts and open questions
Drawing and document intake with revision checks
Engineering-request triage and routing

Where people stay in control

Engineering approves technical interpretation and every controlled change. The tool cites sources and flags uncertainty.

08 · Function

Plant leadership and administration

The information exists, but leaders wait for someone to assemble it from ERP exports, email, meeting notes, and department trackers.

Practical first builds

Daily plant briefing with source links and named owners
Meeting follow-up that tracks decisions and commitments
Plain-language summaries of operating exceptions
Recurring report preparation without retyping the same data

Where people stay in control

Leaders decide priorities and tradeoffs. AI reduces report assembly and makes the underlying evidence easier to inspect.

03 · Across manufacturing

The workflows change by plant. The pattern stays familiar.

Different manufacturing models create different bottlenecks. We do not force the same package onto every operation.

Job shops and contract manufacturers

RFQ intake, quoting history, revision control, job status, outside processing, and customer follow-up.

Discrete assembly and OEMs

Part shortages, supplier promises, work instructions, engineering changes, quality actions, and shift coordination.

Process and batch manufacturing

Batch records, deviation intake, production notes, material status, recurring loss analysis, and controlled procedures.

Food, beverage, and packaging

Checks, sanitation records, holds, shift handoffs, downtime notes, audit evidence, and production reporting.

Industrial products and fabrication

Customer requirements, drawings, cut lists, scheduling changes, purchasing, inspection, and order status.

Industrial distribution and service

Order intake, quote follow-up, product search, supplier coordination, shipment updates, and service documentation.

04 · Three places to begin

A starting system should be easy to picture.

These are examples, not a fixed product catalog. Each one is shaped around your data, rules, systems, approvals, and team.

01 · Starting system

Quote Desk

Turn a crowded RFQ inbox into a complete, review-ready estimating queue.

01 Email and attachments arrive
02 Key fields and gaps are extracted
03 Estimator reviews
04 Quote status stays visible

02 · Starting system

PO Follow-Up

Keep every supplier promise, overdue line, and next action in one working view.

01 Supplier email arrives
02 PO and date are matched
03 Buyer approves follow-up
04 ERP or tracker is updated

03 · Starting system

Shop Knowledge

Make approved procedures, past problems, and experienced answers easier to find.

01 Question is asked
02 Approved sources are searched
03 Answer includes citations
04 Expert corrects or approves

05 · How we deploy

Learn it with the team. Build it in the work.

The forward-deployed model is simple: stay close enough to the process to understand what the software has to survive after the demo.

Step 01

Learn the work

We sit with the people doing the job and follow the real path, including workarounds, exceptions, approvals, and the systems nobody puts in a process map.

Step 02

Choose one useful loop

We pick a narrow workflow with a clear owner, enough examples to test, and a result the team can recognize. No giant transformation program.

Step 03

Build in the current stack

The first version works with the email, documents, spreadsheets, ERP exports, and approval rules already in place. Humans review the steps that require judgment.

Step 04

Train, measure, and support

We train each role on the live workflow, watch where it breaks, tune it from real use, and hand over clear operating documentation. Then we decide together whether to expand.

06 · Your starting point

You do not need a smart factory to start.

The first useful build should match the operation you have today, not the architecture diagram someone wishes you had.

Paper and inboxes

Start with capture and visibility. Digitize one form, inbox, or handoff before adding prediction or autonomous action.

ERP plus spreadsheets

Keep the ERP. Connect the manual work around it: emails, attachments, approvals, explanations, and exception follow-up.

Connected but overloaded

Use AI to summarize, route, search, and surface exceptions. The goal is fewer screens and faster decisions, not another dashboard.

07 · Featured project

Project Foundry, a production and manufacturing assistant.

Project Foundry turns manufacturing problems into focused AI workflows. It starts with production-buyer work and reaches across the plant.

Project Foundry · Working pilot

Built to help manufacturing plants run better.

Working pilot

Project Foundry connects operating facts, messages, documents, and open commitments. The Command Center is where a person asks questions, reviews the evidence, sees what changed, and approves the actions that require judgment.

SKILL 01

Supplier Email Triage

SKILL 02

Supplier Acknowledgment Control

SKILL 03

Evidence-Backed Order Status

SKILL 04

Production Buyer Open-Loop Control

Explore Project Foundry

08 · Working examples

See what the workflow looks like when it is built.

These examples show the problem, the system shape, and where the person doing the job stays involved.

Supply Chain

How to See the Status of Every Open PO Without Digging Through Your Inbox

Supply Chain

How Production Buyers Manage Every Task and Action Item Across Email, Slack, and Teams

Supply Chain

The Morning Briefing That Tells You Exactly What to Act On

Supply Chain

How to Automatically Follow Up on Every Past Due PO the Morning It Appears

See all case studies →

09 · Common questions

What manufacturers usually want to know first.

Do we need clean data before we start?

You need enough real examples to understand the workflow and test a useful first version. A small project often exposes exactly which data needs cleanup, without turning cleanup into a year-long prerequisite.

Does this replace our ERP or MES?

Usually, no. Most first projects connect the work around those systems: email, documents, approvals, explanations, and follow-up. Replacing a core system is a different decision.

Will AI make production or quality decisions on its own?

Not where judgment, safety, quality, compliance, price, or customer commitments are involved. We design explicit human checkpoints and show the source behind the recommendation.

What does the first engagement look like?

We map the workflow, identify the owner and decision points, review examples, and define a narrow first build. You leave the assessment with a practical starting point whether or not we build it together.

What happens after launch?

We train the team, monitor exceptions, correct rules and prompts, and document how the system runs. We can stay involved for support or hand it off cleanly.

Want to think through a workflow before booking a call? Take the free AI assessment.

Walk us through your operation.

Show us the inbox, spreadsheet, form, queue, or handoff eating the team's time. We'll tell you honestly what AI can help with, what should stay human, and what to build first.

Start a conversation Take the free AI assessment →