# AI for SOLIDWORKS PDM: Ask Your Vault and Your ERP the Same Question

> Source: https://netray.co/erp-ai/solidworks-pdm-ai-integration
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: AI for ERP

## Short answer

SOLIDWORKS PDM stores CAD files, revisions, workflow states and BOMs in a vault backed by an archive server and a SQL database. AI helps most on the metadata and process around the files: finding parts and where-used, explaining BOM differences between revisions, reviewing change workflows, and checking that PDM data and the ERP item master agree.

## Kind

platform

## Erp Family

mfg-systems

## Erp Products

- SOLIDWORKS PDM

## Industries

- Discrete Manufacturing
- Industrial Machinery
- Aerospace
- Electronics

## Region

Global

## Persona

Engineering Manager

## Eyebrow

SOLIDWORKS PDM + private AI

## Intro

For many mid-sized manufacturers, the PDM vault is where engineering truth lives and the ERP is where purchasing and production truth lives. SOLIDWORKS PDM Professional keeps files in an archive server, tracks metadata in a SQL Server database, applies workflow states such as In Work, Pending Approval and Released, and calculates BOMs from file references. The ERP then needs an item, a BOM and often a revision that match.

Those two worlds drift. A part is released in PDM with a changed description, but the ERP item still carries the old one. A where-used question that matters before an engineering change takes an engineer an hour of clicking through reference trees. A BOM comparison between revision B and C is possible, but reading and explaining the differences is manual work.

Engineering data is also among a manufacturer's most sensitive intellectual property, and often export-controlled. Sending CAD metadata, part descriptions or drawings to a public AI service is not something most engineering managers are willing to approve.

This page covers what AI on top of SOLIDWORKS PDM realistically does, how it connects without damaging the vault, and where the built-in search, tasks and reports are already enough.

## Pain Points

### Finding the right part is slower than redesigning it

**Detail:** Search by file name and a few data card fields works if you know what to look for. Engineers frequently draw a new part because they cannot confirm that an equivalent already exists and is released.

### Where-used and impact questions take too long

**Detail:** Before changing a part, you need to know which assemblies, drawings and customer products reference it. Reference trees across deep structures are tedious to read and easy to misjudge.

### PDM and ERP item data drift apart

**Detail:** Descriptions, units, revisions, materials and make-or-buy flags are maintained in two systems. Differences surface as purchasing errors, wrong BOM explosions or failed audits.

### ECO and workflow bottlenecks are invisible

**Detail:** Items stuck in Pending Approval or waiting on a particular approver are visible only if someone looks. Release delays quietly hold up production and quotes.

### Engineering IP cannot go to public AI

**Detail:** Part structures, materials, tolerances and customer-specific designs are competitive assets, and often export-controlled, which rules out consumer AI tools.

## Use Cases

### Natural-language part search

**Description:** Engineers describe what they need in plain words and get matching released parts with revision, state, material and where-used counts, drawn from vault metadata.

**Erp Objects:** Vault documents, data card variables, revision and state

**Outcome:** Raises reuse of existing parts and reduces duplicate part creation.

### Where-used impact summary

**Description:** Given a part, the assistant summarizes affected assemblies, drawings and open ECOs and flags the ones tied to active customer orders in the ERP.

**Erp Objects:** References, BOM, ERP sales orders and work orders

**Outcome:** Faster, more complete impact assessment before a change is proposed.

### BOM revision comparison

**Description:** The assistant compares two revisions of a BOM and explains differences in plain language, including added components, quantity changes and substitutions.

**Erp Objects:** PDM BOMs, revisions, ERP BOM

**Outcome:** Reduces manual diffing and helps reviewers focus on meaningful changes.

### PDM to ERP consistency check

**Description:** An agent compares released PDM parts with ERP item masters and lists mismatches in description, unit of measure, revision and material for engineering and master data staff to resolve.

**Erp Objects:** PDM variables, ERP item master, BOM

**Outcome:** Finds drift continuously instead of during audits or after errors.

### ECO workflow monitoring

**Description:** The assistant reports which documents are stuck in a workflow state, for how long and with whom, and drafts reminders for review.

**Erp Objects:** Workflow states, transitions, approvers

**Outcome:** Shortens release cycle time by making bottlenecks visible.

### Change description drafting

**Description:** From the differences between revisions, the model drafts a change description and reason for an ECO, for the engineer to edit.

**Erp Objects:** Revision history, ECO fields, comparison results

**Outcome:** More consistent change records with less writing effort.

### Legacy data cleanup

**Description:** The assistant proposes standardized descriptions and flags missing or inconsistent data card values for a data steward to approve before bulk updates.

**Erp Objects:** Data card variables, descriptions, material and finish fields

**Outcome:** Supports vault cleanup ahead of an ERP migration or consolidation.

## Architecture

**Overview:** The vault stays the system of record. The AI layer reads metadata through supported interfaces, indexes it for retrieval, and joins it with ERP data. It does not write to the vault except through explicit, human-approved actions using supported APIs.

**Layers:**

#### PDM metadata access

**Detail:** Reads document metadata, references, revisions and states through the SOLIDWORKS PDM API from a service account. Read-only SQL against a replica of the vault database is sometimes used for bulk indexing, but it sits outside the documented API, so treat it as a deliberate and tested choice.

#### ERP join

**Detail:** Read-only access to ERP item master, BOM and order tables to compare with PDM data and assess impact.

#### Retrieval index

**Detail:** Indexes metadata and, where policy allows, extracted text from drawings. Controlled data is partitioned by project or classification.

#### Model serving

**Detail:** Open-weight models served locally with vLLM or Ollama on engineering-controlled GPUs.

#### Governance

**Detail:** Permissions mirror vault permissions as far as practical, and every query and suggestion is logged. Bulk changes require approval.

## Deployment Options

### On-prem next to the archive server

**Fit:** Manufacturers with on-site PDM and export-controlled designs.

**Detail:** The AI services run on the same network segment as the vault, with no outbound path for engineering data.

### Private cloud

**Fit:** Companies with a hosted PDM environment or multiple sites.

**Detail:** A dedicated tenant under the company's cloud agreement, with vault replication or API access across sites.

### Metadata-only first

**Fit:** Teams starting cautiously.

**Detail:** Index only data card metadata and BOMs, leaving drawings and CAD geometry out until policies are confirmed.

## Compliance

### Keeping technical data on controlled infrastructure, with access restricted as your program requires, supports your obligations. The determination remains yours.

**Framework:** ITAR and EAR

### Where designs are CUI, place the AI environment inside the same enclave and include it in your system security plan and logging.

**Framework:** CMMC and NIST SP 800-171

### Private processing helps demonstrate that customer designs are not sent to third-party AI services.

**Framework:** Customer IP clauses

### AI-drafted descriptions are labeled as drafts and approved by the engineer, keeping accountability with named people.

**Framework:** Engineering change records

## Integration Notes

- Use a dedicated service account in the vault with the minimum permissions needed for read access.
- Prefer the supported PDM API for metadata; if you index from a database replica, document it and retest after each PDM upgrade.
- Be careful with computed BOMs: confirm which BOM definition, configuration and revision the ERP expects before comparing.
- Map PDM variables to ERP fields explicitly, including units of measure and revision conventions.
- Respect vault permissions in retrieval, or restrict the assistant to roles that may see all indexed data.
- Bulk updates, such as description standardization, run as reviewed batches using supported tools, never as direct database edits.

## Product Fit

### DataRay

**Why:** Chatting across vault metadata, BOMs, ERP tables and engineering documents on-prem is a direct fit for DataRay.

### Custom build

**Why:** Consistency agents, ECO monitoring and change drafting depend on your data cards, workflows and ERP mapping, so they are built to fit.

## Engagement

### Discovery

**Duration:** 2-3 weeks

**Deliverables:**

- Vault structure and data card review
- PDM to ERP field mapping
- Classification of controlled data
- Ranked use cases

### Pilot

**Duration:** 5-7 weeks

**Deliverables:**

- Part search and where-used on a vault subset
- Consistency check against ERP
- Accuracy review with engineers

### Production

**Duration:** 4-6 weeks

**Deliverables:**

- Deployment on controlled infrastructure
- Permission and audit controls
- ECO workflow reporting
- User training

### Expansion

**Duration:** Ongoing

**Deliverables:**

- Additional vaults or sites
- Data cleanup batches
- Model updates
- Quarterly review

## Buyer Questions

- Do you access the vault through the supported API or the SQL database, and what happens at the next PDM upgrade?
- How do you respect vault permissions in retrieval results?
- Which BOM and configuration does the comparison use, and how is that chosen?
- Can it run with no outbound internet access for export-controlled designs?
- How do you prevent write-back from damaging the vault?
- How is accuracy of part search and mismatch detection measured?
- What load does indexing place on the archive and SQL servers?
- What do we keep if we end the engagement?

## Faq

### Can AI read CAD geometry in SOLIDWORKS PDM?

**Answer:** Metadata, references, BOMs and drawing text are far more tractable than geometry. Geometry-based similarity search is a specialized problem and usually handled by dedicated tools. Most value comes from metadata and process data, which a language model can reason about with ordinary retrieval.

### Is it safe to connect to the vault?

**Answer:** With a read-only service account, supported interfaces and an off-peak indexing schedule, the risk is low. Any write action should go through supported tools after human approval, never through direct database edits.

### How does this differ from PDM search?

**Answer:** Built-in search is good for known attributes. A private AI layer adds natural-language queries, summarization of where-used and BOM differences, and joins with ERP data that PDM alone does not hold.

### Does it work with SOLIDWORKS PDM Standard?

**Answer:** Standard has a more limited architecture and API surface than Professional, so capabilities depend on what you can access. Discovery would confirm the integration path before any commitment.

### Can it help with an ERP migration?

**Answer:** Yes. Consistency checks and cleanup suggestions for descriptions, units and material fields reduce the manual effort of aligning PDM and ERP item data before cutover, though data stewards still approve changes.

### What about 3DEXPERIENCE?

**Answer:** If you are moving to 3DEXPERIENCE Works, the same pattern applies with different interfaces. Data modeling and retrieval remain largely reusable; the connector changes.

### Is AI necessary for a small vault?

**Answer:** For a small team with clean data, built-in search and a few saved queries may be enough. AI pays off with many revisions, multiple sites, or a persistent PDM and ERP mismatch problem.

## Search terms

SOLIDWORKS PDM AI, AI for PDM, SOLIDWORKS PDM ERP integration, PDM BOM comparison AI, SOLIDWORKS PDM where used, private AI engineering data, PDM to ERP item master sync, SOLIDWORKS PDM API, ECO workflow AI, engineering change AI SOLIDWORKS, on-prem AI for CAD data, PDM data cleanup AI

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