# AI for Acumatica in Metal Fabrication: Heat Lots, Remnants and Routing Answers From Live Data > Source: https://netray.co/erp-ai/acumatica-metal-fabrication-ai > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: AI for ERP ## Short answer AI for Acumatica in metal fabrication uses Acumatica's contract-based REST API and OData generic inquiries to let estimators, planners and quality staff ask about heat-lot traceability, remnant stock, routing times and job costs in plain English. A private model reads under an Acumatica role, shows the data source for each answer and can run on your own servers beside a cloud ERP. ## Kind industry ## Erp Family other ## Erp Products - Acumatica Manufacturing Edition - Acumatica Cloud ERP - Acumatica Distribution ## Industries - Metal Fabrication - Sheet Metal - Contract Manufacturing ## Region Global ## Persona Operations Manager ## Eyebrow Acumatica + fabrication AI ## Intro Metal fabricators live on thin margins and tight lead times. A shop quoting laser, press brake, weld and finishing work on steel, stainless and aluminium needs fast answers: what is the current price per pound on 11-gauge, how many sheets and remnants are in stock, how long did the same part take last time, and which heat lot went into the job a customer is now questioning. Acumatica stores those facts, but they sit in different forms. Acumatica Manufacturing Edition offers bills of material, routings, work centers, production orders and shop floor tracking, and its open API and generic inquiry engine make data reachable. That is a strong foundation. What fabricators typically lack is a quick, non-technical way to ask cross-cutting questions without building yet another generic inquiry for each one, or waiting for the implementation partner. Quality and compliance add weight. Customers in structural, pressure, defense and aerospace work require mill test reports, heat numbers on parts and sometimes domestic melt origin. Welding programmes may follow AWS D1.1 or ISO 3834, and structural steel exports need EN 1090 documentation. The ERP can hold the lot linkage, but finding it quickly during an audit is where time disappears. This page explains how a private AI layer over Acumatica works for fabrication: the objects it reads, concrete use cases, honest limits (it will not nest parts or replace your CAM software), and how to deploy it so drawings, customer pricing and certificates stay under your control. ## Pain Points ### Heat-lot traceability under audit **Detail:** Linking mill test reports to heat numbers, to cut sheets, to production orders and to shipped parts requires lot tracking discipline and fast retrieval. Customers audit this for structural and defense work. ### Remnants are invisible **Detail:** Partial sheets and offcuts exist physically but are often not tracked in a usable way, leading to repurchase of material that was already on the floor. ### Quoting uses stale cost and time data **Detail:** Estimators rely on memory for routing times and recent material prices, so quotes drift from actual costs, especially with volatile steel and aluminium prices. ### Actual versus estimated time is hard to see **Detail:** Shop floor time posted to production orders is rarely compared against routing standards in a way that supervisors can use during the week. ### Report requests queue behind the partner **Detail:** Every new question becomes a generic inquiry or Report Designer request, and the people who can build them are few. ## Use Cases ### Heat-lot to shipped part trace **Description:** Enter a heat number and see the sheets or bars received, production orders that consumed them, parts produced and customer shipments, plus the linked mill test report reference. **Erp Objects:** Lot and serial tracking on stock items, receipts, production order material transactions (Manufacturing Edition), shipments, attached MTR documents **Outcome:** Audit and complaint traces assembled in minutes, subject to lot discipline at receiving and issue. ### Remnant and offcut search for new jobs **Description:** Before purchasing sheet, the agent searches remnant lots by material, thickness and size that could fulfil a requirement. **Erp Objects:** Stock items by lot and location, item attributes for gauge and grade, warehouse locations, production order demand **Outcome:** Reduced repurchase of material already on hand, depending on how well remnants are captured. ### Estimate versus actual routing time **Description:** Planners ask for the last ten runs of a part number and how actual run and setup hours compare to the routing. **Erp Objects:** Production orders, operations and labor transactions, routings, work centers **Outcome:** Estimates grounded in history; routings updated by people, not automatically. ### Quote support from recent history **Description:** Estimators get similar past quotes and jobs for a part family with material cost, finishing and margin context. **Erp Objects:** Estimates, sales quotes, sales orders, production order cost summaries, purchase receipts **Outcome:** Faster, more consistent quoting; pricing decisions stay with the estimator. ### Late job and bottleneck explanation **Description:** Supervisors ask why a job is late and the agent reviews open operations, material availability and work center load. **Erp Objects:** Production order status, operation queues, work center capacity, purchase order due dates **Outcome:** Faster triage in morning meetings; scheduling optimisation still belongs in your planning tool. ### Purchased finishing and outside processing tracking **Description:** Buyers query which jobs are out for plating, powder coat or heat treat and when they are due back. **Erp Objects:** Purchase orders for outside operations, receipts, production order links **Outcome:** A reliable status view without phoning vendors for every job. ### Material price and usage trends **Description:** Purchasing asks how price per pound of 304 stainless and mild steel plate moved over the last year, and usage by customer. **Erp Objects:** Purchase receipts and invoices, stock issues, item classes **Outcome:** Evidence for surcharge discussions and buying decisions. ## Architecture **Overview:** A private model translates questions into calls to Acumatica's contract-based REST API or OData generic inquiries under a restricted role, then composes answers only from returned data and shows the source. **Layers:** #### API access **Detail:** Contract-based REST endpoints and OData-exposed generic inquiries, optionally a reporting database replica for heavy analytics, authenticated as a dedicated least-privilege user or OAuth client. #### Generic inquiry library **Detail:** A curated set of inquiries for lots, production orders and costs, built so the AI reads defined views rather than arbitrary tables. #### Private model **Detail:** Open-weight model served locally with vLLM or Ollama beside a cloud or hosted Acumatica instance. #### Document index **Detail:** Retrieval over mill test reports, weld procedures, drawings and customer specifications with citations. #### Governance **Detail:** Role mapping, logging of questions and API calls, rate limits that respect Acumatica API limits, and human approval for any suggested change. ## Deployment Options ### Private model beside cloud Acumatica **Fit:** Shops on Acumatica Cloud wanting data control for documents **Detail:** Model hosted on a local GPU server calls the Acumatica API over TLS; documents never leave your site. ### Self-hosted Acumatica with on-prem AI **Fit:** Fabricators running Acumatica on their own infrastructure **Detail:** Everything inside the plant network, reading from a reporting replica for heavy queries. ### Partner-supported rollout **Fit:** Shops relying on an Acumatica reseller **Detail:** The reseller builds the generic inquiries and training while Netray provides the AI stack. ## Compliance ### Helps retrieve welder qualifications, procedure references and material records faster. Qualification control stays with your welding coordinator. **Framework:** AWS D1.1 and ISO 3834 weld quality ### Supports locating heat numbers and certificates linked to parts; factory production control remains your system. **Framework:** EN 1090 and structural steel traceability ### Retrieves recorded melt origin from certificates and lot data when available. It flags missing data instead of assuming. **Framework:** DFARS specialty metals and domestic melt origin ### Local inference and role-based access keep drawings and quotes from public AI services. **Framework:** Customer drawing and pricing confidentiality ## Integration Notes - Use a dedicated Acumatica user with minimal roles and read-only access to the screens needed for the pilot. - Build generic inquiries for lots, production costs and routing history; expose them via OData for stable, versioned access. - Respect Acumatica API limits by caching slow-changing data and scheduling heavy pulls outside peak hours. - Standardise item attributes for material grade, gauge and finish so remnant search is reliable. - Attach mill test reports to receipts or lots consistently so retrieval can cite the exact file. - Test against customised screens and fields in your customization projects before expanding scope. ## Product Fit ### ERPray **Why:** Natural-language answers and dashboards over Acumatica production, inventory and cost data with visible sources. ### DataRay **Why:** Chat across mill test reports, weld procedures and drawings held on file shares. ### Custom build **Why:** A remnant-matching or quote-history agent shaped to your estimating process. ## Engagement ### Discovery **Duration:** 1-2 weeks **Deliverables:** - Question list from estimating, planning and quality - Acumatica API and generic inquiry audit - Hosting and data policy decision ### Foundation **Duration:** 2-3 weeks **Deliverables:** - Least-privilege API user - Curated generic inquiries - Private model environment ### Pilot **Duration:** 3-4 weeks **Deliverables:** - Heat-lot trace and remnant search - Accuracy check against past audits - Usage and logging review ### Scale **Duration:** Ongoing **Deliverables:** - Estimating support agent - Document index expansion - Regression tests per Acumatica release ## Buyer Questions - Can the vendor trace a real heat number on our data in a proof of concept? - How are Acumatica API limits managed under load? - What happens when we update customization projects or a new Acumatica release? - Can the assistant be limited to specific branches or companies? - How are mill test reports linked and cited? - Does inference run locally or via a vendor cloud? - What is the plan when remnant data is incomplete? - Who maintains the generic inquiries after go-live? ## Faq ### Does it use Acumatica's own APIs? **Answer:** Yes. It reads through the contract-based REST API and OData generic inquiries under a dedicated role, so Acumatica permissions and business logic apply. Heavy analytical workloads can use a reporting replica to avoid API strain. ### Can it nest parts or schedule the laser? **Answer:** No. Nesting and shop scheduling belong in CAM and planning software. The assistant answers questions about data in Acumatica, such as remnants available, routing history and job status. It can inform those tools but does not replace them. ### How reliable is heat-lot tracing? **Answer:** It is only as reliable as your lot capture. If heat numbers are recorded at receiving and carried through issues, tracing is fast and accurate. If not, the assistant flags the gap. A pilot often reveals process fixes that improve traceability itself. ### Is our cloud Acumatica data safe? **Answer:** The model runs on your own hardware, and the assistant calls the API over encrypted connections with a restricted identity. Prompts and retrieved documents stay on your side. You remain subject to Acumatica's cloud terms for data held there. ### Will it replace our estimator? **Answer:** No. It gives estimators faster access to similar jobs, current material cost and past actual times. Pricing judgement, customer relationships and risk decisions remain with them. The goal is more consistent quotes and less time digging. ### What does a pilot cost in effort? **Answer:** Expect a few weeks of part-time involvement from one quality person, one planner and one IT contact. The largest effort is agreeing on definitions and building the inquiries, not training a model. ### Can it write to Acumatica? **Answer:** Not by default. Write actions, if ever enabled, are proposals reviewed by a user and executed through standard API calls so audit history stays intact. ## Search terms Acumatica metal fabrication AI, Acumatica manufacturing edition AI, heat lot traceability ERP, metal fabrication ERP AI assistant, Acumatica REST API AI, Acumatica generic inquiry OData, mill test report traceability, remnant tracking ERP sheet metal, Acumatica production orders routing, private AI Acumatica, fabrication quoting AI, Acumatica natural language query --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json