# Epicor Kinetic AI for Metal Fabrication: Jobs, Heat Numbers and Outside Processing in Plain English > Source: https://netray.co/erp-ai/epicor-kinetic-metal-fabrication-ai > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: AI for ERP ## Short answer AI for Epicor Kinetic in a metal fabrication shop lets estimators, planners and quality leads ask questions about jobs, materials, heat numbers, outside processing and quotes in plain English and get answers grounded in live Kinetic data, with the query shown. It runs on-prem or in a private cloud, is read-only by default, and respects Kinetic security so customer drawings, pricing and material certs stay inside your boundary. ## Kind industry ## Erp Family epicor ## Erp Products - Epicor Kinetic ## Industries - Metal Fabrication - Sheet Metal - Job Shops ## Region Global ## Persona Operations Manager ## Eyebrow Kinetic + fabrication shops ## Intro A fabrication shop is a pile of small decisions made against a moving background: a laser that is booked solid, a press brake with a changeover that eats the morning, a coil of 304 that arrived with the wrong mill cert, and a powder coat vendor who is running a week behind. Epicor Kinetic holds the facts behind all of it, in job heads, job materials, job operations, part lots and purchase orders, but getting a straight answer usually means a BAQ someone wrote two years ago or an export to Excel. The questions that actually move the day are cross-cutting. Which open jobs are waiting on the same outside process? Which jobs consumed material from a heat that a customer has just flagged? Which quotes were won at a margin far below what the actual job cost turned out to be? Each one touches four or five Kinetic tables and a naming convention that only your senior planner remembers. Kinetic's own search, Data Discovery and BAQ tooling are good at known questions. They are less good at the open question asked at 7:15 on a Tuesday by a supervisor who does not know which table holds the answer. A language layer over the same data, with the same security, fills that gap without replacing anything you already trust. This page covers what that looks like in a fabrication environment: the Kinetic objects involved, how a private model is deployed beside your database, where it helps estimators, planners and quality staff, and where a plain BAQ or dashboard is still the better tool. ## Pain Points ### Quoting from history is manual **Detail:** Estimators price new work by remembering similar parts. The actual cost of past jobs sits in job material, labor and operation records, but comparing a new DXF or STEP part to history means opening old jobs one at a time. ### Material traceability is slow when it matters **Detail:** When a customer asks which heat number went into which shipped lot, answering means walking part lots, material issues and shipments by hand. Mill test reports often live as scanned PDFs outside the ERP. ### Outside processing hides late jobs **Detail:** Galvanizing, plating, anodizing and powder coat are subcontract operations tracked through purchase orders and job operations. A vendor slipping three days is visible only if someone cross-checks PO receipts against the job schedule. ### Scheduling truth lives in the heads of two people **Detail:** Machine groups, setup sequences, nesting batches and remnant sheets are scheduled by experience. When those two people are out, the board in Kinetic stops being a reliable guide. ### Scrap and remnant data is under-used **Detail:** Nesting software knows utilisation, Kinetic knows cost, and the two rarely meet. Questions like which customer's parts generate the most scrap by material grade stay unanswered. ## Use Cases ### Historical job cost lookup for quoting **Description:** An estimator describes the part family, material and quantity and asks what similar jobs actually cost versus quoted, with the jobs listed so the estimator can verify the match. **Erp Objects:** Erp.JobHead, Erp.JobMtl, Erp.JobOper, Erp.QuoteDtl, Erp.QuoteMtl, Erp.QuoteOper **Outcome:** Faster quote turnaround on repeat-pattern parts and fewer under-priced jobs, since actual cost is checked rather than recalled; the estimator still sets the price. ### Heat number and lot traceability **Description:** Quality asks which shipped orders contain material from a given heat or lot and gets a traced list from material issue to job to shipment. **Erp Objects:** Erp.PartLot, Erp.LotSelectedTracking, Erp.JobMtl, Erp.ShipDtl, Erp.OrderRel **Outcome:** A traceability answer that takes minutes of review instead of hours of table walking, with the supporting records listed for audit. ### Outside processing watchlist **Description:** A buyer asks which jobs are blocked on subcontract operations that are past their promised return date and gets the PO, vendor and affected customer orders. **Erp Objects:** Erp.POHeader, Erp.PODetail, Erp.PORel, Erp.JobOper (subcontract), Erp.OrderRel **Outcome:** Earlier visibility on late subcontract work so expediting happens before the customer calls. ### Machine group load and bottleneck check **Description:** A planner asks which work centers carry the heaviest queue over the next two weeks and which jobs are driving it. **Erp Objects:** Erp.JobOper, Erp.JobHead, Erp.ResourceGroup, Erp.Resource **Outcome:** A quicker read on where overtime or outsourcing will be needed, as a decision aid rather than an automatic reschedule. ### Scrap and rework by customer and material **Description:** A manager asks which customers and material grades generate the most scrap cost and gets a ranked, drillable result. **Erp Objects:** Erp.LaborDtl, Erp.JobMtl, Erp.NonConf, Erp.Part, Erp.Customer **Outcome:** Evidence for price adjustments or process fixes, grounded in booked scrap rather than anecdote. ### Late order explanation **Description:** Customer service asks why a specific order is late and gets the chain: material availability, operation status, subcontract return, or quality hold. **Erp Objects:** Erp.OrderHed, Erp.OrderRel, Erp.JobHead, Erp.JobOper, Erp.PODetail **Outcome:** Customer replies that cite the real reason, drafted from live records and reviewed by a person. ### Drawing and spec retrieval with ERP context **Description:** A retrieval layer indexes drawings, mill certs, weld procedure specs and customer quality requirements so a question returns the document and the part and job it relates to. **Erp Objects:** Erp.Part, Erp.PartRev, Erp.JobAsmbl, attached documents and file shares **Outcome:** Less time hunting through folders for the right revision or certificate; the source document is always cited. ## Architecture **Overview:** A private model and a retrieval layer run beside Kinetic, never inside it. Questions are translated into constrained read queries over Kinetic through REST or a read replica, executed under the asking user's rights, and returned with the generated query visible. **Layers:** #### Kinetic data access **Detail:** Read-only access through Kinetic REST (OData v2 service endpoints and BAQs) or a SQL Server read replica. Curated BAQs for sensitive joins keep column access explicit. #### Semantic layer **Detail:** A mapped vocabulary of fabrication terms (heat, nest, remnant, outside op, work center) to Kinetic tables and user-defined fields, maintained with your planners so the model stops guessing. #### Document retrieval **Detail:** Indexes of drawings, mill certs, WPS documents and customer requirements, chunked and linked to part, revision and job numbers, stored on your infrastructure. #### Private inference **Detail:** An open-weight model served with vLLM or Ollama on your GPUs or sovereign cloud. No prompt or result goes to a public API. #### Governance and audit **Detail:** Per-user permissions mirrored from Kinetic security, query logging, and human approval before any write-back such as a BPM-routed update. ## Deployment Options ### On-prem next to Kinetic **Fit:** Shops running Kinetic on their own SQL Server with ITAR or customer NDA constraints **Detail:** A single GPU server on the plant network reaches the database over an internal link; nothing leaves the building. ### Private cloud tenant **Fit:** Shops on Epicor-hosted or self-managed Azure who want AI in their own subscription **Detail:** A model endpoint in your own tenant with private networking to the Kinetic REST layer; you control the keys and the logs. ### Hybrid with a retrieval-only start **Fit:** Shops that want document search first and ERP questions later **Detail:** Start with drawings and certs on a file share, then add Kinetic query access once the semantic layer is agreed. ## Compliance ### Architecture keeps technical data on infrastructure and personnel you designate; the customer determines whether their setup meets their ITAR obligations. **Framework:** ITAR and EAR for defense parts ### The assistant is read-only and cites source records, so it supports retrieval of controlled documents without altering them. **Framework:** ISO 9001 and AS9100 records ### Weld procedure and welder qualification documents are indexed with source citations; the model never certifies compliance itself. **Framework:** AWS D1.1 and ISO 3834 weld documentation ### Private inference means drawings are not sent to a third-party AI service, which many customer NDAs forbid. **Framework:** Customer NDAs on drawings ## Integration Notes - Use a dedicated Kinetic API user or per-user token with a least-privilege security group; do not reuse a manager account. - Prefer BAQs for cross-table reads such as job cost versus quote, so joins and column access are reviewed once and reused. - Map user-defined columns (UD fields) on JobHead, Part and PartLot in the semantic layer; fabrication shops store heat, grade and finish there often. - Index attached documents from the file share or Kinetic attachments with the part and revision as metadata. - Expect SQL Server read replica load to be modest; schedule heavy analytical questions off peak. - Write-back, if used, should go through Kinetic business objects and BPM method directives, with a person approving each change. ## Product Fit ### ERPray **Why:** Natural-language questions and dashboards over live Kinetic jobs, materials and orders, with query visibility and role-aware access. ### DataRay **Why:** Chat across drawings, certs and file shares alongside Kinetic data when documents are the bigger problem. ## Engagement ### Discovery **Duration:** 1-2 weeks **Deliverables:** - Top 20 questions from estimating, planning, quality and purchasing - Kinetic version, hosting and security review - Data classification for drawings and certs ### Semantic layer and security **Duration:** 2-3 weeks **Deliverables:** - Fabrication vocabulary mapped to tables and UD fields - Read-only service account and BAQ set - Permission model matching Kinetic security groups ### Pilot with one team **Duration:** 3-4 weeks **Deliverables:** - Working assistant for estimating or planning - Accuracy test set with expected answers - Usage and miss log reviewed weekly ### Expand and harden **Duration:** Ongoing **Deliverables:** - Added teams and document sources - Monitoring, model update and rollback plan - Runbook for your IT staff ## Buyer Questions - Does every answer show the exact query or records it used? - Does the assistant run under the asking user's Kinetic rights, or a shared account? - Where do drawings and mill certs get processed, and is any of it sent to a third-party model? - How are user-defined fields and shop-specific terms handled? - What happens if the model is wrong on a traceability question? - Can we run it without internet access? - What does it cost to run per year in GPU and support terms? - Who maintains the semantic layer when we change Kinetic? ## Faq ### Does this replace Epicor Kinetic reports and BAQs? **Answer:** No. BAQs and dashboards remain the right tool for known, repeated questions. The language layer handles the open questions nobody built a report for, and it can call your existing BAQs rather than bypass them. Many shops find the assistant also shows which new BAQs are worth building. ### Can it help with quoting? **Answer:** It can retrieve how similar past jobs actually cost versus what was quoted, and list those jobs for the estimator to verify. It does not set prices or approve quotes. Pricing judgement, customer relationship and capacity context stay with the estimator. ### How does it handle heat number traceability? **Answer:** It traverses part lots, material issues, job material and shipments in Kinetic and lists the records it used. It is a fast lookup, not a certification. Any answer used for a customer or audit response should be checked against the underlying records. ### Is our drawing data sent to a public AI service? **Answer:** No. The model runs on your hardware or in your own private cloud tenant, and retrieval indexes are stored there too. This matters for customer NDAs and export-controlled drawings. We recommend verifying the network path during pilot. ### Do we need Epicor Cloud or can this work on-prem Kinetic? **Answer:** Both work. Self-hosted Kinetic offers direct read-replica options, while Epicor-hosted cloud usually means going through the REST API and BAQs. The REST route is slower for heavy analytics but keeps you within what Epicor supports for your hosting arrangement. ### What hardware do we need? **Answer:** A pilot for a small team often runs on one workstation-class or server GPU with a mid-sized open-weight model. Sizing depends on concurrent users and document volume, so we size it during discovery using your question mix rather than guessing up front. ### Can it write back to Kinetic? **Answer:** It can, but read-only is the default and we suggest staying there for months. If you add write-back, changes go through Kinetic business objects and BPM rules with a person approving each one, and every action is logged. ## Search terms epicor kinetic metal fabrication ai, ai for sheet metal fabrication erp, epicor kinetic heat number traceability, epicor kinetic quoting ai, private ai for fabrication shop, epicor kinetic outside processing, on-prem llm epicor, epicor kinetic natural language query, epicor kinetic baq ai, fabrication erp ai assistant --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json