InforIndustry

SyteLine + metal fabrication

AI on Infor SyteLine for Metal Fabricators: Quotes, Heat Lots, Routings and Job Cost

Short answer

AI on Infor SyteLine for metal fabricators connects a private model to SyteLine estimates, jobs, routings, heat and lot data and purchasing so estimators and operations managers can find comparable past jobs, trace material to mill certs, and explain job cost variance in plain English. It runs on-prem or privately, shows each query, and drafts without writing to SyteLine unless a person approves.

ERP: Infor SyteLine, Infor CloudSuite Industrial
Industries: Metal Fabrication, Job Shops, Industrial Equipment
Written for: Operations Manager / Estimator

Discuss your Infor SyteLine environment See use cases

Metal fabrication shops sell on quote speed and delivery. A typical shop cuts on a laser or plasma table, forms on press brakes, welds, finishes and sometimes sends parts out for powder coat or plating. In SyteLine this appears as jobs with multi-operation routings, work centers for each machine group, steel and component material lines, and outside processing operations tied to purchase orders. The data to estimate well exists, but it sits in past jobs that nobody has time to search.

Estimators often quote from memory or a similar-looking old job. The questions that matter are specific: what did the last five brackets of this size and material actually cost, how long did the weld and finish operations really take compared to the routing, and what did we pay for this plate last quarter? SyteLine can answer them, but only after someone builds the right report or exports the data.

Traceability is the second pressure. Structural and pressure work needs mill test reports and heat numbers (for example EN 10204 3.1 certificates), weld procedure and welder records under standards such as AWS D1.1 or EN 1090, and customers ask for certificates of conformance after delivery. Linking heat and lot numbers through cut, form and weld to a shipped assembly is the kind of trace a private AI layer can shorten.

Fabricators often cannot send drawings or customer pricing to a public AI tool. This page explains what a private, read-only AI layer on SyteLine does for a fab shop, and where nesting software, a quoting tool or a CAD/PLM integration remains the right answer.

What usually gets in the way

The problems we hear most from operations manager / estimator teams running Infor SyteLine.

Quoting relies on memory and old jobs

Finding comparable past jobs by material, thickness, process mix and quantity means navigating job history and exports. Estimators default to gut feel when the quote is due today.

Routing time versus actual labor

Weld, grind and finish operations often overrun the routing. The gap is visible in labor transactions but rarely summarized per part family, so estimates keep repeating the same error.

Heat and lot traceability across operations

Material gets cut into multiple parts and remnants. Without disciplined lot handling, tracing a heat number to a shipped weldment is slow and uncertain.

Outside processing delays hide in plain sight

Parts sent for coating or heat treatment sit on POs with promised dates that nobody reviews systematically, delaying downstream operations and shipments.

Steel price volatility

Plate, sheet and tube prices move between quote and purchase. Comparing quoted, standard and actual cost per job requires data from estimates, POs and job material issues.

Where AI earns its place in Infor SyteLine

Each use case names the ERP objects it reads or writes, so your ERP team can judge the integration effort before anyone commits budget.

Comparable job lookup for estimators

An estimator describes a part (material, thickness, size, process) and the assistant retrieves similar past jobs with quantity, actual hours by operation and material cost, ready to adjust.

Touches: job, jobroute, jobtran, jobmatl, item, estimate or quote records

Outcome: Quicker, better-supported quotes; the estimator keeps full control of pricing.

Routing versus actual hours review

By part family or work center, the agent compares routed and actual hours and flags operations with persistent overruns.

Touches: jobroute, jobtran, wc, item

Outcome: Evidence for updating routing standards instead of arguing from anecdotes.

Heat number to shipment trace

Given a heat or lot number, the assistant lists jobs consuming it, the assemblies produced and the customers shipped to.

Touches: lot, matltran, jobmatl, job, serial or lot output, coitem, shipment lines

Outcome: Faster response to a certificate request or material nonconformance; quality verifies the chain.

Outside processing watchlist

The agent lists open outside operations by vendor with promised versus needed dates, and drafts follow-up messages for the buyer to send.

Touches: jobroute (outside ops), po, poitem, po_rcpt, vendor

Outcome: Fewer late surprises on coating and heat treat; one view replaces several screens.

Job cost variance explanation

For a completed job, the assistant breaks down estimate versus actual by material, labor, outside processing and scrap, noting what moved most.

Touches: job, jobmatl, jobtran, poitem, estimate

Outcome: A faster post-job review that feeds back into the next quote.

Remnant and drop utilization

Where remnants are tracked as inventory, the agent suggests existing sheet remnants matching upcoming jobs for planners to consider.

Touches: item (remnant items), lot_loc, jobmatl, planned jobs

Outcome: Some reduction in new plate purchases; actual savings depend on remnant discipline.

Certificate of conformance drafting

For a shipment, the agent assembles material cert references and job data into a draft CoC for quality to review and issue.

Touches: lot, matltran, job, coitem, ship records, document references

Outcome: Removes manual lookup; quality still signs.

Reference architecture

The AI layer sits next to SyteLine and reads estimating, job and inventory data through IDO REST, with document retrieval over mill certs and drawings held in a file share or document system. Outputs are drafts and answers; SyteLine remains the system of record.

1
SyteLine connector
Scoped IDO REST user for jobs, routings, lots and purchasing, with an optional read replica for history analysis.
2
Document retrieval
Private index over mill certs, weld procedures and customer drawings on your file share, linked to jobs and lots by reference number.
3
Semantic layer
Maps work centers to machine groups (laser, brake, weld, finish), materials to grades and thicknesses, and your user-defined fields.
4
Model serving
Open-weight models on your own GPUs or in a private tenant; no drawings or customer pricing sent to public APIs.
5
Governance and audit
Per-user query logs, read-only default and approval for drafted POs, quotes or certificates.

Integration notes for your ERP team

Jobs, routings and labor transactions are read through IDOs; the connector does not assume a standard operation naming scheme.
Heat numbers are normally tracked via lots; discovery checks whether yours are lot-controlled or only on paper before trace answers are trusted.
Mill certs and drawings are indexed from the file share and linked by heat, lot or job number, not by guesswork on file names.
Estimating data is read from SyteLine estimate or quote records when used; shops using external quoting tools need an export or API link.
Outside processing is read from routing operations flagged as outside and their linked purchase orders.
Drafted quotes, POs and certificates are saved to a review queue, never posted straight to SyteLine.

Deployment options

On-prem

Job shops handling customer drawings under NDA or defense subcontract terms.

Model, index and connector run on a server in your facility with no outbound AI traffic.

Private cloud

CloudSuite Industrial customers with several plants.

Dedicated tenant connected over private networking; access mapped to SyteLine roles.

Hybrid

Fabricators with estimators remote from the shop.

Question layer reachable securely off-site while data and models stay on the plant side.

Compliance and data control

How the architecture supports your obligations. Certification and accountability stay with your organisation; the design keeps the evidence straightforward.

AWS D1.1 / EN 1090 / ASME fabrication records

Helps retrieve weld, procedure and material records you already maintain; qualification and sign-off stay with your welding and quality staff.

EN 10204 material certificates

Links heat numbers to jobs and shipments so certificates can be located and referenced; it does not create or alter mill certs.

ITAR and defense subcontracts

On-prem deployment keeps controlled drawings and part data inside an environment you define as approved.

Customer NDA terms

No drawings or pricing reach a third-party AI service, which simplifies answers to customer security reviews.

Where Netray fits

ERPray

Estimator and operations questions over jobs, hours and cost are well suited to grounded natural-language querying and dashboards.

SyteRay

Suitable for custom SyteLine reports such as routing-versus-actual or certificate templates.

DataRay

Useful when cert PDFs, drawings and spreadsheets need to be searched together with ERP data.

How an engagement runs

Phase 1 . 2-3 weeks

Discovery

-Review of job, routing and lot practices in SyteLine
-Document source inventory (certs, drawings)
-Estimator and ops interviews
-Use case ranking and deployment recommendation

Phase 2 . 6-8 weeks

Pilot

-Comparable job lookup and heat trace live on a test copy
-Accuracy review with estimators
-Document index built for a sample customer set
-Role-based access check

Phase 3 . 4-6 weeks

Production

-Production cutover
-Outside processing and variance use cases
-Audit logs and runbooks
-User training

Phase 4 . Ongoing

Scale

-More plants and customers
-CoC draft workflow
-Model refresh and regression checks
-Quarterly accuracy review

Questions to ask any vendor, including us

A short list that separates real Infor SyteLine AI work from a chatbot demo.

How does the system decide a past job is comparable, and can the estimator see why?
How are heat numbers tied to lots in our setup and what happens where they are not?
Are drawings and customer pricing ever sent outside our network?
Does it integrate with our nesting software or only read SyteLine?
Can it show actual hours by operation for a part family without a custom report?
How is document retrieval kept in sync when new certs are added?
What is written back to SyteLine, and who approves it?
When would you tell us a quoting tool is the better answer?

Frequently asked questions

Can AI generate quotes in SyteLine?

It can assemble comparable past jobs, actual hours and material costs to support an estimator, and draft a quote for review. Fully automated quoting from drawings is a separate, harder problem and needs CAD or nesting integration; we would scope that as a custom build.

Does it replace nesting software?

No. Nesting optimizes material use on the cutting table. The AI layer works on ERP data: jobs, costs, lots and purchasing. They complement each other, and nesting output can feed job data in SyteLine.

How reliable is heat number tracing?

It depends on whether heats are recorded as lots through cutting and issue. If lot discipline is weak, the assistant will show gaps rather than hide them, and the fix is a process change.

Can it read mill certificates?

Yes, if they are stored digitally and indexed. It extracts heat numbers and properties for lookup and linking. Extraction accuracy is checked in the pilot because scanned certificate quality varies.

Is it useful for a small job shop?

Often yes for estimating and outside processing, provided SyteLine is used consistently. If jobs are rarely closed accurately, cleaning that up delivers more than any AI layer.

How does outside processing follow-up work?

The agent lists operations awaiting vendors, compares promised to needed dates, and drafts messages. A buyer reviews and sends them. It does not email vendors by itself.

What about CloudSuite Industrial?

The approach is the same via supported APIs. Heavy history queries may use API paging or an approved replica depending on your hosting arrangement.

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