Manufacturing SystemsERP Platform

ETQ Reliance + private AI

AI for ETQ Reliance: Joining Your Quality Records to Your ERP Data

Short answer

AI for ETQ Reliance reads the records quality teams already keep in ETQ (CAPA, nonconformance, complaints, audits, supplier corrective actions, controlled documents) through its REST API and joins them to ERP lots, work orders and supplier data. It answers questions such as which CAPAs trace to one supplier or lot, drafts root-cause summaries for human review, and never closes or approves a record on its own.

ERP: ETQ Reliance
Industries: Manufacturing, Medical Devices, Aerospace, Automotive
Written for: Quality Manager

Discuss your ETQ Reliance environment See use cases

ETQ Reliance is a configurable, largely no-code QMS used by manufacturers in medical devices, aerospace, automotive and electronics. Its strength is that quality teams can build and change forms, workflows and approvals themselves. The side effect is that every deployment ends up with its own field names, lookup lists, custom forms and escalation rules, so two ETQ sites inside the same company rarely look identical.

The harder problem is not inside ETQ. A nonconformance record points at a part number, lot, work order or supplier, but the facts that explain it (receiving inspection, routing step, scrap transactions, purchase order terms, shipment history) live in the ERP. Quality engineers rebuild that context by hand for every CAPA, copying values between screens and spreadsheets, which is slow and error prone.

Reliance has its own reporting and analytics, and ETQ continues to add vendor-side AI features. For questions that stay inside ETQ, those may be enough. The case for a separate layer appears when you need cross-system answers, when you must keep record content inside your own network, or when the QMS is one of several systems (MES, PLM, ERP) that a single question has to span.

This page describes what AI on top of ETQ Reliance realistically does, which integration surfaces it uses, how it respects ETQ permissions and electronic-record rules, and which questions to put to any vendor before connecting a model to your quality system of record.

What usually gets in the way

The problems we hear most from quality manager teams running ETQ Reliance.

CAPA context is assembled by hand

An engineer opening a CAPA still has to pull lot genealogy, supplier history, similar past events and inspection data from other systems. Most of the effort in a CAPA is evidence gathering, not decision making.

Free-text root causes are impossible to trend

Problem statements and root-cause narratives are written by different people in different words. Pareto charts by category miss the pattern that the same failure appears under three different labels.

Configuration drift between sites

No-code configurability means each site customises forms and workflows. Cross-site reporting needs mapping tables that someone has to maintain, and nobody owns them.

Audit preparation is a manual sweep

Before an ISO 13485, AS9100 or IATF 16949 surveillance audit, teams export lists of overdue actions, expired documents and open supplier CARs, then reconcile them in a spreadsheet.

QMS and ERP disagree about the same event

An NCR says quantity 40 held, the ERP shows 52 moved to quarantine. Without a join across both, nobody knows which is right until someone investigates.

Where AI earns its place in ETQ Reliance

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

CAPA evidence assembly

For an open CAPA, the assistant gathers related NCRs, supplier records, lot genealogy and prior similar actions into a cited brief the owner can review and edit.

Touches: ETQ CAPA, NCR and Supplier records via REST API; ERP lot master, work order, receipt and PO tables

Outcome: Cuts evidence gathering from hours to minutes per CAPA; the owner still writes and approves the conclusion.

Recurring-defect clustering

Embeds free-text problem descriptions and groups near-duplicates across sites and categories so repeat failures surface even when labelled differently.

Touches: ETQ nonconformance description fields, defect codes, part and supplier references

Outcome: Reveals repeat issues that category-level Pareto charts hide; precision depends on how consistently records are written.

Supplier corrective action drafting

Drafts a supplier CAR from an NCR, pulling the PO, lot, inspection result and past corrective actions for that supplier.

Touches: ETQ Supplier Corrective Action; ERP PO line, receiving inspection, vendor master

Outcome: Faster, more complete first drafts; a quality engineer reviews before anything is sent.

Audit readiness queries

Plain-English questions such as which controlled documents are past review date or which CAPAs exceed their due dates by process area.

Touches: ETQ Document Control, CAPA due dates, Audit findings and action items

Outcome: Replaces export-and-pivot prep with a query that shows its filter and source records.

Complaint to production trace

Starting from a customer complaint, traces to shipped lot, work order, routing steps and component lots in the ERP.

Touches: ETQ Complaint; ERP shipment, lot genealogy, work order operations, component issues

Outcome: Faster containment scoping; completeness depends on ERP lot tracking discipline.

Training and document impact checks

When a controlled document changes, lists affected processes, roles and work centers so training and effectivity can be planned.

Touches: ETQ Document Control and Training assignments; ERP routing and work center data

Outcome: Fewer missed training assignments; the QMS workflow still enforces the actual approvals.

Management review packs

Assembles trend summaries of CAPA aging, complaint rates and audit findings with links back to source records.

Touches: ETQ CAPA, Complaint, Audit modules; ERP scrap and yield summaries

Outcome: Saves analyst time before management review; numbers stay traceable to records.

Reference architecture

A read-only service layer authenticates to ETQ Reliance through its REST API with a scoped service account, syncs the records it needs into a private index, and joins them to ERP data through a read-only connector. A model served inside your boundary answers questions and drafts text, citing the source record IDs. Any write to ETQ goes through a human-approved step.

1
ETQ connector
Uses the Reliance REST API with a least-privilege service account. Respects ETQ permissions so the assistant cannot read records the requesting user could not.
2
ERP connector
Read-only access to lot, work order, receipt, PO and shipment data through the ERP's API or a replicated reporting schema.
3
Private index and RAG
Structured fields stay in SQL for exact filters; narrative fields are embedded for similarity search. Both are stored in your environment.
4
Model serving
Open-weight model such as Llama, Qwen or Mistral class served with vLLM or Ollama on your GPUs or private cloud, with prompts and outputs logged for audit.
5
Review and approval
Drafts are saved as proposals. A named user reviews and submits them in ETQ, so the electronic signature and audit trail belong to a person.

Integration notes for your ERP team

ETQ Reliance exposes a REST API; confirm which version and which modules your licence and tenant expose before scoping.
Use a dedicated service account with read scopes limited to the modules in scope, and review its permissions as forms are re-configured.
Map custom form and field names once into a semantic layer so questions do not depend on each site's labels.
Join keys matter: agree on how part number, lot, work order and supplier ID appear in ETQ so the ERP join is deterministic, not fuzzy.
Treat attachments (photos, PDFs, 8D reports) as a separate ingestion stage with OCR and size limits.
Plan for incremental sync using modified-date filters rather than nightly full pulls.
If ETQ is hosted by the vendor, document the network path and approval needed for your private environment to call it.

Deployment options

Read-only pilot beside ETQ

Teams validating value before wider rollout

A synced, read-only index of selected modules (CAPA, NCR, Supplier) with a chat and cited briefs. No write-back.

Private cloud or VPC

Regulated companies with a cloud-first policy

Model and index run in your own cloud tenancy. ETQ data moves only between your tenant and the ETQ API.

On-prem or air-gapped model

Defense, aerospace and customers with data-residency clauses

Model and index on local GPUs. Requires a permitted path to fetch ETQ data, or an export-based sync where direct API access is not allowed.

Compliance and data control

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

FDA 21 CFR Part 11 / QMSR

The assistant does not create or sign records. Electronic signatures stay in ETQ; the AI layer's own prompts and outputs are logged, and the customer validates it under their computer system validation procedure.

ISO 13485 and ISO 9001

Supports document control and CAPA evidence gathering without replacing the controlled process. Outputs are drafts, not records of decision.

AS9100 and IATF 16949

Helps with traceability and audit preparation; nonconformance disposition and customer notification remain human decisions.

ITAR / EAR data handling

Private deployment keeps controlled technical data inside the customer's boundary. The customer remains responsible for registration and access control.

Data protection

Complaint records may include personal data. Role-based filtering and minimisation rules apply before text reaches the model.

Where Netray fits

Custom build

ETQ-specific CAPA briefs, clustering and audit packs are built to your forms, workflows and validation approach.

ERPray

Supplies the ERP side of the join: lots, work orders, receipts and POs with the query shown and ERP roles respected.

DataRay

Useful when quality evidence also sits in file shares, inspection PDFs or lab databases outside ETQ.

How an engagement runs

Phase 1 . 1-2 weeks

Discover

-Module and form inventory for ETQ
-Join-key map between ETQ and ERP
-Top five question list from quality engineers
-Data classification and access review

Phase 2 . 3-4 weeks

Prototype

-Read-only index of selected ETQ modules
-ERP lot and supplier join
-CAPA evidence brief with citations

Phase 3 . 3-4 weeks

Validate

-Test set of known CAPAs with expected answers
-Accuracy and refusal review with quality staff
-Validation documentation inputs for your CSV process

Phase 4 . Ongoing

Operate

-Monitoring of answer quality and drift after form changes
-Access review cadence
-Backlog of next modules to add

Questions to ask any vendor, including us

A short list that separates real ETQ Reliance AI work from a chatbot demo.

Which ETQ modules and API endpoints does the integration read, and with what permissions?
Does the assistant ever write to ETQ, and if so who signs the record?
How does it handle our custom forms and per-site field differences?
Where do model, index and logs run, and can records stay inside our boundary?
How do you measure answer accuracy against known CAPAs before go-live?
What happens to the integration when we reconfigure a workflow?
How do you support our computer system validation expectations?
When is ETQ's own reporting or AI enough for us?

Frequently asked questions

Can AI close CAPAs in ETQ Reliance automatically?

It should not. CAPA closure involves effectiveness checks and signatures that regulators expect a responsible person to own. A sound design lets the assistant gather evidence, draft text and flag overdue items, while a named user reviews, edits and signs in ETQ itself.

Do we need AI if ETQ already has analytics?

For questions that stay inside ETQ, its reporting and any vendor AI features may be enough. A separate layer pays off when you need to join quality records to ERP lots, suppliers and work orders, or when policy requires the model to run inside your own environment.

How does the integration connect to ETQ?

Through the Reliance REST API using a scoped service account, with incremental sync of the modules in scope. Exact endpoints and fields depend on your version and configuration, so the first step is an inventory of the forms you actually use.

Can it run without sending data to a public AI service?

Yes. Open-weight models are served on your GPUs or in your private cloud, and the index lives in your environment. The only external traffic is between your environment and the ETQ API, which you control and can document for auditors.

How accurate are the root-cause suggestions?

Suggestions are hypotheses drawn from similar past records and ERP evidence, not conclusions. Accuracy depends on record quality and consistent join keys. We test against a set of historical CAPAs with known outcomes and report where the assistant should decline to answer.

Does this affect our validated state?

If the assistant is read-only and does not create or sign records, it usually sits outside the validated QMS workflow, but your quality unit decides how to classify it. We supply design and test documentation to support your own computer system validation procedure.

How long does a pilot take?

A read-only pilot over CAPA, NCR and supplier modules with an ERP join typically takes several weeks, depending on API access approvals and how consistent your form configuration is across sites. Access approvals are usually the long pole, not model work.

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