Cetec ERP + private AI
AI for Cetec ERP Electronics Manufacturing
Short answer
AI on Cetec ERP means grounding a private model on Cetec's browser-native, all-in-one data (quoting, MRP, shop floor, quality) so EMS and PCB shops can get natural-language answers on job genealogy, cost rollups, and NCR history, deployed in a way that keeps customer BOMs and IP-sensitive program data off any shared or public AI service.
- ERP
- Cetec ERP
- Industries
- Electronics Manufacturing, PCB Assembly, Contract Manufacturing
- Written for
- IT Director
Cetec ERP has carved out a niche as the lower-cost, browser-native alternative to bigger ERPs for electronics contract manufacturers and PCB assembly shops: quote-to-cash, MRP, shop floor execution, and quality in one web app, priced per user per month with no client install. That breadth is exactly why EMS shops choose it, and exactly why the AI opportunity is broader than a single module.
EMS work runs on traceability and IP discipline. A job traveler documents exactly which components, lots, and operators touched a given assembly; a customer BOM often cannot leave the shop's control; and a program running under a defense prime's contract usually carries ITAR or EAR obligations that rule out sending any of that data to a public AI service, no matter how convenient.
Most Cetec shops are small to mid-size, often without a dedicated data or BI team, so quoting engineers redo cost rollups by hand, quality staff dig through screens for NCR history during an audit, and program managers manually trace which open jobs an engineering change actually touches.
This page covers what AI on Cetec ERP looks like in practice: how it grounds on job traveler and genealogy data, what an EMS shop needs to hear about export control before deploying anything, and where an air-gapped pattern earns its keep.
What usually gets in the way
The problems we hear most from it director teams running Cetec ERP.
Customer BOMs and program data cannot go to a public AI
Customer-owned BOMs, drawings, and program-specific process notes are frequently covered by NDA or export control, which rules out any AI tool that sends data to a shared, third-party model API.
Genealogy and traceability lookups eat engineering time
Tracing which finished assemblies used a specific component lot, or reconstructing a job's full history for a customer audit, means digging through several Cetec screens manually.
Quoting engineers redo cost rollups by hand
Should-cost and quote turnaround depend on current component pricing and labor standards, which quoting staff often recalculate outside Cetec because pulling a clean rollup is slow.
NCR and RMA drafting is repetitive and inconsistent
Writing up a nonconformance or RMA in the format an auditor or customer expects takes time and varies by who writes it, which is a real finding risk during an AS9100 or ISO audit.
ECO impact analysis is manual and error-prone
When an engineering change lands, figuring out which open jobs, WIP, and purchase orders it actually affects requires cross-referencing BOM revisions and open orders by hand.
Where AI earns its place in Cetec 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.
Natural-language job traveler and genealogy Q&A
Engineers and quality staff ask which lots or serials went into a given assembly, or which finished units contain a specific suspect component lot.
Touches: Job Traveler, Work Order, Lot/Serial tracking, BOM
Outcome: Cuts a genealogy investigation from a multi-screen manual trace to a direct, cited answer.
Quote cost rollup and should-cost assistant
An agent pulls current component pricing, labor standards, and BOM structure to produce a should-cost estimate a quoting engineer reviews before sending a quote.
Touches: BOM, Purchasing pricing history, Labor/Routing standards, RFQ
Outcome: Shortens quote turnaround and reduces reliance on a spreadsheet kept outside Cetec.
NCR and RMA drafting copilot
The agent drafts a nonconformance or RMA writeup in the shop's standard format, grounded on the actual job, part, and customer history, for quality staff to review.
Touches: NCR/CAPA records, RMA, Job Traveler
Outcome: Improves writeup consistency ahead of AS9100 or ISO audits and cuts drafting time.
Engineering change impact analysis
When an ECO lands, the agent lists the open jobs, WIP, and purchase orders affected by the BOM or routing change so program management does not have to trace it manually.
Touches: Engineering Change Orders, BOM revisions, Work Orders, Purchase Orders
Outcome: Reduces the risk of a change being missed on an open job during a busy production week.
PO and expedite follow-up agent
The agent drafts follow-up messages for late purchase orders on components holding up a job, referencing the actual PO and program due date.
Touches: Purchase Orders, Suppliers, Job due dates
Outcome: Turns ad hoc expediting into a reviewed, prioritized, ready-to-send list.
RFQ intake triage
Incoming customer RFQs are summarized and matched against similar past jobs to give sales and quoting a faster starting point.
Touches: RFQ/Quote history, BOM library, Customer records
Outcome: Speeds up initial RFQ response without skipping the engineering review step.
Shop floor work instruction assistant
Operators ask what a step in the job traveler means or what the current revision of a work instruction requires, grounded in the live document rather than a printed copy that may be out of date.
Touches: Job Traveler, Work Instructions, Document revisions
Outcome: Reduces reliance on printed instructions that can drift out of sync with the current revision.
Reference architecture
Because Cetec ERP is browser-native and API-accessible, the connector layer pulls quoting, MRP, shop floor, and quality data through Cetec's REST API into a private store, with the semantic layer paying particular attention to genealogy and program-level access boundaries.
- 1
Cetec ERP connectors
Read access to Cetec's REST API across quoting, purchasing, MRP, shop floor, and quality modules, pulled into a private, customer-controlled data store.
- 2
Semantic layer
Maps Cetec's job traveler, genealogy, and BOM structures to the terms engineers and quality staff use, and enforces program-level data boundaries between customers.
- 3
Model serving
An open-weight model served entirely on customer-controlled infrastructure, with no outbound connection required once deployed for air-gapped configurations.
- 4
Retrieval and agents
Grounded question answering plus narrow agents (NCR drafting, ECO impact lists, PO follow-up) that produce a draft or list for a human to review, not an automatic write-back.
- 5
Governance and audit
Every answer cites the specific job, lot, or record it used, with an audit trail suited to AS9100, ISO 9001, or customer program review.
Integration notes for your ERP team
- Cetec ERP exposes a REST API across its modules; this is the primary integration path for pulling quoting, MRP, shop floor, and quality data into a private store.
- Job traveler and genealogy data structures need careful mapping in the semantic layer, since these are the highest-value and highest-scrutiny queries in an EMS context.
- Program-level access segregation, keeping one customer's program data from surfacing in answers scoped to another, needs to be enforced at the semantic layer, not assumed from Cetec's own user permissions alone.
- Cetec ERP is a hosted, browser-native system; deployments handling export-controlled data pull data out to an isolated on-prem environment rather than assuming Cetec's own hosting meets that requirement.
- Purchasing price history and labor/routing standards both need to be current for should-cost estimates to be trustworthy, so the connector should pull these on a short refresh cycle, not a weekly batch.
- Document revision control for work instructions should be respected exactly: a shop floor assistant must always reference the current revision, never a cached older version.
Deployment options
Air-gapped on-prem
EMS shops running ITAR- or EAR-controlled programs, or handling NDA-protected customer BOMs
Scheduled pulls mirror Cetec data into an isolated on-prem environment with no outbound network path, so customer BOMs, program data, and genealogy never reach any shared or public infrastructure.
Private cloud
Shops without export-control obligations that still want data control beyond a public model API
The connector, data store, and model run in a private VPC the customer controls, with the same read-only, no-write-back pattern as the air-gapped option.
Hybrid
Shops running a mix of commercial and program-restricted work
Commercial-program data flows through a private cloud deployment while ITAR- or NDA-restricted programs are isolated in a separate air-gapped instance with strict segregation between the two.
Compliance and data control
How the architecture supports your obligations. Certification and accountability stay with your organisation; the design keeps the evidence straightforward.
ITAR / EAR
Technical data tied to export-controlled programs never leaves the customer's network; the air-gapped pattern is the default recommendation for any Cetec shop with defense or export-controlled work.
AS9100 / ISO 9001
NCR, CAPA, and traceability answers cite the underlying job and lot records, supporting the objective evidence an auditor expects rather than an unsourced summary.
Customer NDA and IP protection
Customer-owned BOMs and drawings stay within the customer-controlled deployment; program-level access boundaries prevent one customer's data from surfacing in answers about another.
CMMC / NIST 800-171 (for DoD-adjacent programs)
The same on-prem, no-outbound-connection architecture used for ITAR data aligns with the data protection expectations behind CMMC and NIST 800-171 controls, without claiming a certification the customer has not independently obtained.
Where Netray fits
ERPray
Grounded natural-language question answering over Cetec's quoting, MRP, shop floor, and quality data fits ERPray's model directly.
Custom build
Genealogy-specific agents, program-level data segregation, and NCR/RMA drafting tuned to a shop's exact quality format typically require a custom build on top of the same connectors.
How an engagement runs
Phase 1 . 2 weeks
Discovery
- -Review of Cetec module usage and which programs carry ITAR/EAR or NDA restrictions
- -Assessment of current genealogy, quoting, and NCR/RMA workflows and where time is lost
- -Data segregation requirements across customers and programs
Phase 2 . 5-7 weeks
Pilot
- -Connectors and semantic layer covering job traveler, genealogy, BOM, and quality data
- -Natural-language question answering validated on real genealogy and quoting questions
- -One agent (NCR drafting or ECO impact analysis) running in review-before-use mode
Phase 3 . 3-4 weeks
Production
- -Air-gapped or private-cloud deployment matched to each program's export-control status
- -Program-level access segregation validated against real customer and program boundaries
- -Audit trail configured to support AS9100/ISO 9001 objective evidence requirements
Phase 4 . ongoing
Scale
- -Additional agents added for quoting, expediting, or shop floor support
- -Coverage extended to additional programs as segregation rules are validated
- -Periodic review against evolving CMMC or customer flow-down requirements
Questions to ask any vendor, including us
A short list that separates real Cetec ERP AI work from a chatbot demo.
- Does the AI layer ever write back into Cetec ERP, or is every action a draft for human review?
- For ITAR/EAR-covered programs, does any technical data leave our network at any point, including for model updates?
- How is data segregated between customer programs within the same Cetec instance?
- Can the system show exactly which job, lot, or record it used to answer a genealogy question?
- How are NCR/RMA drafts and their AI assistance documented for audit purposes?
- Is pricing structured around a small EMS shop's headcount, or built for a much larger enterprise?
- Who is accountable if an AI-assisted cost rollup or genealogy answer turns out to be wrong?
Frequently asked questions
Is it safe to use AI on ITAR-controlled Cetec data at all?
It can be, if the deployment is air-gapped: the model and all program data run entirely on the customer's own network with no outbound connection, so nothing that would constitute a deemed export ever leaves the facility. Sending the same data to a public AI API is the pattern to avoid.
Does Cetec ERP have built-in AI already?
Cetec ERP's strength is being a browser-native, all-in-one system covering quoting through shop floor and quality without a client install, not a native generative AI layer. A private AI layer adds natural-language question answering and drafting agents grounded in Cetec's own data.
How does this handle multiple customer programs in one Cetec instance?
The semantic layer enforces program-level boundaries so that a question scoped to one customer's program cannot surface another customer's BOM, cost, or genealogy data, which is treated as a hard requirement, not an optional setting.
Can AI actually speed up genealogy investigations?
Yes. Once grounded on job traveler and lot/serial data, a question like which finished assemblies contain a specific component lot resolves in seconds with a cited answer, instead of the manual multi-screen trace engineers do today.
Will this help with AS9100 or ISO 9001 audits?
It helps with the documentation burden: NCR and CAPA drafts are grounded in the actual job and lot records, and answers used in preparing for an audit carry a citation back to the source records, which supports the objective evidence an auditor expects.
Does the AI replace quoting engineers?
No. It produces a should-cost estimate and cost rollup draft from current pricing and labor standards that a quoting engineer reviews and adjusts before it goes into a customer quote, saving the manual recalculation step rather than removing engineering judgment.
How long does a Cetec ERP AI pilot take for an EMS shop?
A working pilot covering genealogy and quoting question answering plus one agent typically takes five to seven weeks, longer than a simpler MRP tool, because export-control review and program-level data segregation need to be validated before production use.
Related guides
Natural Language Query for ERP Data: Ask SAP, Infor, or Oracle a Question in Plain English
See how natural language query over SAP, Infor, Oracle, and NetSuite data works: grounded text-to-SQL, role-based permissions, and a visible audit trail.
RAG + SQL + permissionsA Private LLM Grounded on Your ERP Data
How a private LLM answers questions on your ERP data: RAG plus text-to-SQL, role-based permissions inherited from the ERP, and where each fits.
Agents + approval gatesAI Agents for ERP, Running On-Prem
A practical guide to on-prem AI agents for ERP: what they can safely automate, where human approval belongs, and how to design the guardrails.
ERP AI Buyer GuideHow to Choose an ERP AI Implementation Partner
A CIO checklist for picking an ERP AI implementation partner: the architecture questions to ask, red flags, pricing models, and what to demand in the SOW.
QAD + on-prem AIAI for QAD Adaptive ERP in automotive and industrial manufacturing
Add AI to QAD Adaptive ERP or Enterprise Edition for automotive and industrial manufacturing, grounded on QXtend and QAD's API layer, on-prem or private cloud.
Plex + private AIAI for Plex Manufacturing Cloud, Grounded in Your Production Data
Put AI on Plex production, quality, and genealogy data without a public model. On-prem or private-cloud LLMs, RAG, and agents built for Plex shops.
Plan it with numbers
Electronics Traceability Readiness Checklist
A 30-point checklist to audit your lot/serial capture, supplier traceability, test data linkage, and recall readiness before a customer or auditor does.
Free ToolITAR AI Workload Compliance Assessment
Score your AI deployments across eight dimensions of ITAR exposure, from technical data classification and US persons access control to technology control plan coverage.
Free ToolERP AI Copilot ROI Calculator
Turn user count, query volume, and time saved per question into a monthly savings, license cost offset, and payback period for an ERP AI copilot.
GuideAI-Powered Quoting for Aerospace & Defense Manufacturers
AI-powered quoting for aerospace and defense manufacturers: cut quote turnaround from weeks to days while handling ITAR data, DFARS clauses, and cost buildup.
GuideITAR-Compliant AI Tools for Manufacturing: Requirements and Options
ITAR-compliant AI tools for manufacturing: what export control rules mean for LLMs, which vendors qualify, and how to deploy AI without a deemed-export risk.
GuideYour First AI Agent: A Manufacturing Playbook
Your first AI agent in manufacturing: pick a bounded ERP use case, scope data access, set guardrails, and ship a working pilot in 6 to 8 weeks.
Talk it through with an engineer who knows Cetec 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.