ProShop + medical device machining
AI for ProShop ERP in Medical Device Machining: Traceability, NCRs and Audit Readiness
Short answer
AI for a ProShop medical device machining shop reads work orders, NCRs, CAPAs, tool and gauge records and lot data so quality managers can answer traceability and audit questions in plain English. Because ProShop is cloud-hosted, data is pulled through its API into a model you control, read-only, with every answer tied to a source record.
- ERP
- ProShop ERP
- Industries
- Medical Devices, Precision Machining, Contract Manufacturing
- Written for
- Quality Manager
A contract machine shop that makes implant components, surgical instruments or device housings sells more than parts. It sells records. A customer's supplier quality agreement and the shop's own quality system expect traceable material, validated processes, calibrated gauges, controlled documents and a clean story when an NCR or complaint arises. ProShop was built around this kind of paperless, record-heavy shop.
ProShop ties work orders, part and process records, tooling, gauges, quality inspection, NCRs and CAPAs together in one system, which is its strength. But a quality manager still spends hours before a customer audit pulling together evidence: which lots used a given material heat, which gauges were out of calibration during a period, what actions closed which NCRs, and whether any open item is overdue.
The regulatory backdrop is also moving. FDA's Quality Management System Regulation, which replaced the 21 CFR 820 Quality System Regulation and incorporates ISO 13485:2016 by reference, took effect on February 2, 2026. Contract manufacturers that supply device makers are held to supplier controls through their customers, and customers will be asking for evidence in the ISO 13485 form.
This page describes private AI over ProShop for a medical device machining shop: what it reads, the use cases where it saves quality and production staff time, where ProShop's own search and reports are already sufficient, and what to ask before connecting a model to records that carry customer IP and regulated data.
What usually gets in the way
The problems we hear most from quality manager teams running ProShop ERP.
Audit preparation is a manual evidence hunt
Before a customer or notified body audit, quality staff assemble evidence across work orders, NCRs, CAPAs, calibration records and training. Each audit repeats the exercise.
Lot and material traceability questions are slow under pressure
When a customer asks which finished lots used a particular bar stock heat or which parts were machined on a machine after a tool failure, the answer requires joining several record types quickly.
Calibration and tool status affects inspection validity
If a gauge is found out of tolerance, the shop must identify which inspections relied on it since its last good calibration. That is a time-boxed lookup done under stress.
NCR and CAPA trends are hard to see
Individual NCRs get closed, but patterns by part family, operation or machine are not obvious in a list. Recurring root causes are missed until a customer points them out.
Cloud-only ERP raises data handling questions
ProShop is delivered as a hosted service. Customers with strict IP or data terms want to understand exactly where any additional AI processes their records.
Where AI earns its place in ProShop ERP
Each use case names the ERP objects it reads or writes, so your ERP team can judge the integration effort before anyone commits budget.
Lot and heat traceability query
A quality engineer asks which work orders and finished lots used a given material heat or lot, and which customers shipments they went to, and gets a traceable list with record links.
Touches: Work orders, material receipts, lot and heat numbers, shipments, customer orders
Outcome: Reduces a multi-system lookup to a quick query, which matters when a supplier notifies of a material issue.
Gauge out-of-tolerance impact lookup
Given a gauge found out of calibration, the assistant lists inspections and work orders that used it since the last good calibration, for the quality team to review.
Touches: Gauge and calibration records, inspection records, work orders, operations
Outcome: Speeds a time-critical impact assessment and reduces the risk of missing an affected lot.
Audit evidence assembly
For a stated audit scope such as supplier controls or nonconforming product, the assistant gathers relevant records, open items and closure dates into a draft evidence list for the quality manager to verify.
Touches: NCRs, CAPAs, document control records, training records, calibration, supplier records
Outcome: Cuts the hours spent pulling evidence together; the manager still reviews and decides what to present.
NCR and CAPA pattern review
The assistant groups NCRs by part, operation, machine, tool and cause code, and highlights repeat patterns and overdue CAPA actions.
Touches: NCRs, CAPAs, cause codes, work orders, machines, tool records
Outcome: Surfaces recurring issues earlier than periodic manual review and gives CAPA effectiveness checks real data.
Work order release readiness check
Before releasing a work order, the assistant checks that the required drawing revision, process, tools, gauges and material certs are present and current, and lists gaps.
Touches: Parts, part revisions, process records, tools, gauges, work orders, material certs
Outcome: Catches missing prerequisites before the job reaches the machine, where fixing them costs time and sometimes scrap.
Customer complaint investigation support
For a complaint on a part number or lot, the assistant assembles the production history, inspection results, deviations and related NCRs into a timeline for the investigator.
Touches: Work orders, inspection data, deviations, NCRs, lot records, shipments
Outcome: Shortens the start of an investigation by presenting the facts in one place; conclusions remain with the investigator.
Production status for customer service
Customer service asks where an order stands and whether inspection and certs are complete, without interrupting the floor.
Touches: Work orders, operations, inspection status, shipping and certification records
Outcome: Fewer interruptions for production and quality staff.
Reference architecture
Because ProShop is hosted, the AI layer pulls records through ProShop's supported API or data export into infrastructure you control, indexes them, and answers using a model that runs there. It is read-only, and each answer links to the source records so a quality manager can verify it.
- 1
ProShop connector
Authenticated access through ProShop's supported API or scheduled export, using a dedicated integration user with read-only scope. Available endpoints and fields are confirmed with ProShop for your account.
- 2
Semantic layer
Maps work orders, parts, processes, NCRs, CAPAs, gauges and lots to quality-system vocabulary, including your own cause codes and custom fields.
- 3
Model serving
An open-weight model served with vLLM or Ollama on hardware you own, in a private tenant, or in a customer-controlled cloud region.
- 4
Retrieval and agents
Structured retrieval for traceability and counts, plus document retrieval for attached procedures and certs. Agents draft evidence lists and timelines for human review.
- 5
Governance and audit
Per-user logging, read-only operation, source links on every answer, and exclusions for customers or programs under stricter terms.
Integration notes for your ERP team
- Confirm API access, rate limits and available fields with ProShop for your account before designing the pull.
- Use a dedicated integration user with read-only scope; do not share a staff login.
- Pull on a schedule into a local or tenant store so questions do not hit ProShop live and so answers remain available if the network is down.
- Attachments such as certs and procedures should be indexed only from approved record types and respect the user's role.
- Every answer should cite the record identifiers it used, so a quality manager can open the source in ProShop.
- Treat the AI layer as a tool that supports quality records, and run it through the shop's own software validation procedure before using it in any controlled process.
Deployment options
On-premises replica
Shops that want the model and an indexed copy of records to sit entirely on their own network.
A scheduled pull from ProShop into a local store feeds the AI server. Only the pull crosses the network boundary, not model prompts.
Private cloud tenant
Shops without on-site GPU capacity that have a controlled cloud environment.
A dedicated tenant in a region of your choice, with restricted egress and no shared AI services.
Hybrid with local inference
Shops with a small on-site server for inference and a cloud-hosted index.
Sensitive records stay local while larger non-sensitive indexes live in the private tenant.
Compliance and data control
How the architecture supports your obligations. Certification and accountability stay with your organisation; the design keeps the evidence straightforward.
FDA QMSR (21 CFR Part 820) and ISO 13485:2016
The assistant retrieves and organizes records you already keep, such as supplier controls, nonconforming product and CAPA. It does not make quality decisions, and the quality manager remains responsible for the content and conclusions of any audit response.
21 CFR Part 11 and computer system validation
Where AI is used in a quality process, the shop should assess it under its own software validation procedure. Read-only operation, source-linked answers and audit logs make that assessment simpler; the validation itself is the shop's responsibility.
Customer supplier quality agreements and IP terms
Running the model on infrastructure you control means part data, drawings and process parameters are not sent to a public AI provider, and exclusions can be applied by customer.
UDI and lot traceability expectations
Traceability queries return the lot, work order and shipment links recorded in ProShop, so gaps in the underlying records are visible rather than papered over.
Where Netray fits
ERPray
Plain-English questions and dashboards over ProShop work orders, NCRs and inspection data, read-only and source-linked.
DataRay
Useful when procedures, supplier certs and shared-drive records need to be searched alongside ProShop data on-prem.
Custom build
For an audit evidence assistant or a gauge-impact agent tailored to the shop's own quality system structure.
How an engagement runs
Phase 1 . 2-3 weeks
Discovery
- -ProShop API and export review
- -Quality system record map and data sensitivity review
- -Ranked use cases with quality, production and customer service
- -Validation approach outline
Phase 2 . 6-8 weeks
Pilot
- -Read-only connector and local index
- -Traceability, gauge impact and NCR pattern use cases live
- -Accuracy check against known lots and past audits
- -Source-link and logging review
Phase 3 . 4-6 weeks
Production
- -Audit evidence and release readiness checks rolled out
- -Role-based access
- -Documentation to support the shop's own validation
- -Admin runbook
Phase 4 . Ongoing
Improve
- -Complaint investigation timelines
- -Additional record types
- -Model updates under change control
- -Quarterly accuracy and usage review
Questions to ask any vendor, including us
A short list that separates real ProShop ERP AI work from a chatbot demo.
- How do you obtain data from ProShop, and what scope does the integration user have?
- Where does the model run, and can we show a customer exactly where their part data is processed?
- Does every answer cite the source records so we can verify it?
- How does this fit our software validation procedure and 21 CFR Part 11 considerations?
- Can specific customers or programs be excluded from retrieval?
- How fresh is the data if we pull on a schedule, and what happens if a pull fails?
- Which of these tasks does ProShop's own search and reporting already handle?
- What do we keep if the engagement ends?
Frequently asked questions
Can AI help prepare for an ISO 13485 or customer audit using ProShop data?
It can gather and organize records you already keep, such as NCRs, CAPAs, calibration and supplier records, into a draft evidence list with links to sources. The quality manager verifies it and decides what to present. It does not assess compliance or replace the audit process.
ProShop is cloud-hosted. How does private AI work?
Records are pulled through ProShop's supported API or export into infrastructure you control, indexed there, and answered by a model running there. Only the scheduled data pull leaves ProShop; prompts and answers stay within your environment.
Do we need to validate it?
If it is used in a controlled quality process, the shop should assess it under its own software validation procedure, as FDA expects for software used in the quality system. Read-only operation, cited sources and logging make that easier, but validation remains the shop's responsibility.
Does it handle lot traceability?
It returns the lot, work order and shipment links recorded in ProShop. If the underlying records have gaps, the answer shows the gap rather than guessing, which is useful in itself during an investigation.
Can it make quality decisions?
No. It retrieves, groups and summarizes records and drafts timelines. Disposition of nonconforming product, root cause conclusions and CAPA effectiveness decisions stay with qualified people.
Is our customers' IP sent to a public AI service?
No. The model is open-weight and runs on infrastructure you own or control, with no route to public AI APIs. Specific customers or programs can be excluded if their terms require it.
How long until a pilot is running?
Typically six to eight weeks for a read-only pilot after a two to three week discovery, depending on API access, record quality and how much time the quality team can give for validation of answers.
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Talk it through with an engineer who knows ProShop ERP
Bring one real question your team cannot answer from the ERP today. We will map the data path, the model, and where it runs, and tell you honestly if AI is the wrong tool for it.