AI systems for modern industrial manufacturers.

Operational AI infrastructure for quoting, supplier operations, market intelligence, field service, and engineering knowledge — built around how your business actually runs.

Manufacturing Operations for the AI Era Scroll to explore

You are losing time and revenue in predictable places

We have mapped operations at industrial OEMs, contract manufacturers, and global suppliers. The specifics change. The friction points do not.

Sales intake is a five-day game of phone tag

01

A buyer requests a quote at 9pm. The CSR calls at 11am, leaves a voicemail, emails the rep, who emails the engineer, who emails the buyer back two days later asking for specs. The deal cools while the chain finishes its loop.

Quote turnaround · 3–7 days, intake to first response

RFQ specs arrive in fifty different shapes

02

PDFs, spreadsheets, drawings, hand-marked photos, customer-portal exports — every customer has a different format and every internal team re-keys the same dimensions into ERP, MES, and the quote tool.

RFQ re-keying · 1–3 hrs per inquiry

Market intelligence is a quarterly PowerPoint

03

Competitor moves, trade journals, regulatory shifts, supplier news — the manager assembles a slide deck once a quarter from whatever Google Alerts coughed up. By the time leadership reads it, the move has already happened.

Market signal lag · weeks to months behind

Supplier ops live in three inboxes and a spreadsheet

04

Lead times, quality issues, OTD, claims — tracked in email threads with whoever responds first. Performance reviews happen annually. The chronically late supplier keeps getting purchase orders.

Supplier performance · annual at best, anecdotal

Service technicians spend half the day on paper

05

Field reports, parts pulls, customer signatures, completion notes — captured on a clipboard, transcribed at the truck, lost between truck and office. Warranty claims and parts forecasting get the leftovers.

Tech admin time · 30–45% of field shift

Parts catalogs and tribal knowledge walk out the door

06

The senior engineer who knew which valve fits which line, which alternate part the customer accepts, which assembly drawing is current — retires. Nothing is written down in a system the next hire can search.

Institutional knowledge · concentrated, undocumented

The operational lifecycle of a manufacturer

Before we talk about AI, we map the machine. Every manufacturer we work with starts here — the four operational surfaces every order, unit, and customer touches, and the work that happens on each.

01

Demand & quoting

From inquiry to bound quote. Where lead time wins business — or kills it.

  • Inquiry intake. Web, phone, distributor, portal
  • Spec interpretation. PDF, drawing, photo, spreadsheet
  • Configure & price. Catalog match, options, pricing rules
02

Supply & production

Where promises become parts. The supplier and production layer that defines OTD and margin.

  • Supplier sourcing. RFQ to vendors, compare, select
  • PO + ASN tracking. Lead time, arrival, exception
  • Quality & NCRs. Inbound inspection, root cause
03

Service & after-sales

What happens after the unit ships — and decides whether the customer is a one-time buyer or a fleet account.

  • Service intake. Customer, dispatch, technician match
  • Field service ops. Job docs, parts, signatures, completion
  • Warranty claims. Eligibility, parts, supplier recovery
04

Market & knowledge

Everything that turns activity into insight — competitors, regulations, customer trends, internal expertise.

  • Competitive intelligence. Sites, journals, filings, releases
  • Regulatory tracking. Standards, codes, certifications
  • Customer voice. Service, sales, distributor signals

AI is infrastructure, not a replacement for your engineers and operators

We do not believe in an "AI engineer." We believe in an AI operations layer that takes the predictable, repetitive, system-to-system work off your team so your engineers and operators can spend their time on design, quality, and customer relationships.

AI handles

Repetitive work that slows your team down.

  • Inquiry intake & qualification. Conversational capture across channels, 24/7
  • RFQ spec interpretation. Parse PDFs, drawings, spreadsheets into structured data
  • Quote drafting. Configure, price, format, send — partner reviews
  • Supplier performance tracking. OTD, quality, claims, by vendor, by category
  • Market & competitive scouting. Monitor sources, summarize, deliver on a cadence
  • Field documentation. Voice + photo capture, structured report drafting
  • Parts & knowledge retrieval. Drawings, BOMs, SOPs, prior projects — cited
Your team handles

The judgment, strategy, and relationships.

  • Engineering judgment. Design decisions, tolerances, materials
  • Pricing strategy. Margin calls, deal-specific terms
  • Supplier selection. Strategic vendor relationships, contracts
  • Quality decisions. Reject, accept, NCR disposition
  • Customer relationships. Strategic accounts, escalations, contracts
  • Compliance sign-off. Certifications, standards, audits
  • Anything irreversible. Sent quotes, issued POs, accepted warranty claims

Anything substantive passes through a human.

Sent quotes, issued POs, accepted warranty claims, signed certifications. The AI parses, configures, retrieves, and surfaces — your engineers, buyers, and quality leads decide and sign.

What we actually build

Six systems we have deployed in production at manufacturers. None of them are chatbots in the marketing sense. All of them are operational infrastructure that connects the tools you already use.

System / 01

Inquiry & Quote Engine

Inbound inquiries are qualified, specs are parsed from any format, and a draft quote is on the partner's desk within the hour — not the week.

Outcome

Web

System / 02

Supplier Performance Scorecard

OTD, quality, NCR, and claim performance tracked per supplier across the portfolio — bad performers get the call, good ones get more business.

Outcome

ERP

System / 03

Market Scouting Agent

Trade journals, competitor sites, regulatory feeds, and community discussions monitored continuously — delivered as a newsletter, an intranet chatbot, or both.

Outcome

Web

System / 04

Field Service Documentation

Voice + photo capture from the technician on the truck becomes a structured job report — warranty claims, parts pulls, and customer signatures all linked to the unit.

Outcome

Mobile app

System / 05

Parts & Engineering Knowledge Assistant

Sales reps, technicians, and customers retrieve the right part, the right drawing, the right alternate — in seconds, with citations to the source drawing.

Outcome

PLM

System / 06

Voice-of-Customer Aggregator

Signals from service, sales, distributors, and complaints get clustered into product and operational insights — feeding engineering, marketing, and ops, not just a quarterly slide.

Outcome

CRM

In production.

One example of what we've shipped in the manufacturing space.

Manufacturing · Case study

AI Market Scouting for a Global Industrial OEM

How an industrial OEM deployed an AI market scouting agent that monitors trade journals, competitor sites, and community discussions across 15–30 sources — delivered as a monthly executive newsletter and an SAP-integrated chatbot.

Read the case study →
15–30
Sources monitored
2
Output channels
SAP
Intranet-integrated

Fits into the stack you already run

We do not ask manufacturers to migrate. We build the operational layer on top of the systems you have already invested in — your ERP stays the system of record, your PLM stays the engineering source of truth, and the AI lives in the seams between them.

ERP & MRP

  • SAP
  • Oracle
  • NetSuite
  • Microsoft Dynamics
  • Infor
  • Epicor

PLM & engineering

  • Siemens Teamcenter
  • PTC Windchill
  • Aras
  • Autodesk Vault
  • SolidWorks PDM
  • Custom PLM

Service & field

  • ServiceMax
  • Salesforce Field Service
  • IFS
  • Microsoft FSM
  • MaintainX
  • Custom mobile

Workflow & data

  • EDI
  • Distributor portals
  • Email
  • n8n
  • Slack / Teams
  • Vector DB

How we think about AI inside a manufacturer

01

AI is operational infrastructure.

Not a feature, not a chatbot, not a magic button on a marketing page. The work it does is the same work your team has always done — moved into a system where it runs reliably.

02

Accuracy is the floor.

Manufacturing is a quality business. If a system is not measurably more accurate than your current process, we do not ship it. We measure tolerance fit, OTD, and quote accuracy continuously.

03

Operational fit beats novelty.

The best AI system is the one that disappears into the plant's actual workflow. If your team has to change how they work to use it, it is the wrong system.

04

Humans stay in the loop on engineering and supply.

Design decisions, tolerance disposition, supplier selection, customer escalations — all go through a person. The AI parses, configures, retrieves, and surfaces.

Questions,
answered.

The stuff we hear most on the first call. Don't see yours? Book a 30-minute conversation.

How long does an engagement actually take?
A first system — typically the quoting engine or market scouting agent — is in production inside 4 to 8 weeks. We start with a workflow audit, ship a single high-leverage system end-to-end, and only then expand.
What does this look like for the manufacturer during build?
A weekly working session with operations or engineering leadership, async access to a CSR, technician, or buyer for workflow questions, and read-only credentials into the systems we are integrating with. No new platform to learn until the system is live.
How is engineering and customer data protected?
Data stays inside your existing systems. We do not store manufacturer data in our infrastructure. Models we use are configured to not retain prompts, access is scoped per role and per region, and audit trails are written to your ERP and PLM.
What happens when the AI is wrong?
Every system has a human checkpoint at the substantive step — sending a quote, releasing a PO, signing off on a service report, accepting a warranty claim. The AI prepares and drafts; an engineer, buyer, or service lead accepts.
Do we need to switch off our current ERP or PLM?
No. Your ERP, PLM, service system, and quoting tools — all stay systems of record. We build on top of them. The operational layer is additive.
How is this priced?
Fixed-fee for the initial audit and the first system. Retainer for ongoing operations, optimization, and additional systems. We do not bill hourly for AI work — outcomes, not seat time.

Ready to become
AI-Native?

Book a 30-minute conversation. We'll map the highest-leverage workflows in your business and tell you whether AI is the right answer.