# How to use ChatGPT with Infor VISUAL

> Source: https://netray.co/integrations/infor-visual-chatgpt
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Integrations

## Short answer

There are three ways to use ChatGPT with Infor VISUAL: paste or upload exported data, build a custom GPT whose action calls a small read-only API you host, or run a private model instead. The middle path gives live answers but needs an internet-reachable service in front of a database that is usually on-prem.

## System

Infor VISUAL

## Capability

chatgpt

## Intro

Most VISUAL users first try ChatGPT by exporting a grid to Excel and asking questions about it. That works for one-off analysis, and it is a reasonable way to find out what questions people actually want answered.

The next step is live access. A custom GPT can call an HTTPS API you define, so a planner could ask about a part or a work order and get current numbers. The catch is that VISUAL typically sits on a SQL Server inside the plant, so something has to expose a narrow, authenticated slice of it.

Whether that is acceptable depends on what the data is. Part numbers and open PO status are one thing; customer drawings, ITAR-controlled technical data and pricing are another. This page lays out the options so you can choose with the data in mind.

## Use Cases

### Ad hoc analysis of exported grids

**Description:** Export open order lines or inventory transactions to a spreadsheet and ask ChatGPT to summarize trends, find outliers or draft commentary for a review meeting.

### Order status answers for sales

**Description:** A custom GPT with an action over your API lets a salesperson ask where a customer order stands without opening the Customer Order Entry window.

### Drafting vendor and customer emails

**Description:** Give ChatGPT a PO line or order line summary and have it draft a polite, specific follow-up that a person edits.

### Explaining a bill of materials or routing

**Description:** Paste a structure for a new hire and ask for a plain-language walk-through of what is made, in what order, and where the risks are.

### Writing queries and report logic

**Description:** Use it as a SQL and Crystal formula helper, then test the result against a copy of the database before anyone relies on it.

## System Surface

- Grid exports from VISUAL windows to Excel or CSV, the simplest way to get data into a chat. Quality depends on which columns the window shows.
- The VISUAL SQL Server database, which an intermediary API can query with read-only views. Table names such as CUSTOMER_ORDER, CUST_ORDER_LINE, PART and PURC_ORDER_LINE are common, but check your version.
- Crystal Reports output (PDF or Excel) as a scheduled, already-approved data source for uploads.
- A thin REST service you host that translates a few named calls into read-only SQL. A custom GPT action points at its OpenAPI description.
- Infor ION or toolkit-based interfaces, only if your version exposes them and you need write-back, which is rarely wise from a chat interface.

## How It Works

### Decide what may leave the plant

**Detail:** List the data classes involved: part masters, pricing, customer drawings, export-controlled data. Mark which are allowed in a hosted service at all.

### Start with exports

**Detail:** Use a masked Crystal report or grid export. Remove customer names and prices if they are not needed. Learn what users ask before building anything.

### Build a narrow read-only API

**Detail:** Host a small service with endpoints like order status or part availability. It uses a read-only SQL login, returns limited fields, and rate limits calls.

### Authenticate properly

**Detail:** Use OAuth or a per-user token rather than a shared key in the GPT configuration, so you can tell who asked for what and revoke access.

### Create the custom GPT action

**Detail:** Provide an OpenAPI description, clear instructions on when to call each endpoint, and a rule to say it does not know when a call returns nothing.

### Review the workspace settings

**Detail:** Check your plan's data controls, retention and training settings, and decide whether a business plan or enterprise plan is the minimum your policy accepts.

## Example Flows

### Sales asks about a customer order

**Trigger:** Salesperson types an order number into the custom GPT

**Steps:**

- The GPT calls the order status endpoint.
- The service queries CUSTOMER_ORDER and its lines read-only.
- The response lists line status, promised dates and shipped quantities.
- The GPT summarizes and flags any late line.

**Result:** The salesperson gets a quick current answer, and the call is logged on your side.

### Monthly inventory review prep

**Trigger:** Planner uploads an exported slow-moving inventory file

**Steps:**

- ChatGPT groups items by age and value.
- It proposes candidates for disposal or reorder-point changes.
- The planner checks the shortlist against VISUAL before acting.

**Result:** A review pack is drafted in minutes, and the decisions stay with the planner.

## On Prem

If the data cannot go to a hosted service, ChatGPT is the wrong tool for that data, and a private model is the usual answer. Run an open-weight model on a GPU server inside the plant, put a chat front end and the same read-only API pattern next to your SQL Server, and keep everything on the local network. You can still use ChatGPT for non-sensitive work, such as drafting, while the private model handles anything that touches controlled data.

## Security

- Treat anything pasted into a hosted chat as leaving your network and check plan terms.
- Use read-only credentials and field-limited endpoints behind the custom GPT action.
- Avoid shared API keys; issue per-user tokens you can revoke.
- Never expose write operations to a general chat interface.
- Do not upload export-controlled technical data to a general hosted service unless your compliance team has approved it.

## Options

### Manual exports into a business plan workspace

**Fit:** Occasional analysis with non-sensitive data.

**Effort:** Hours to set a routine, no development.

### Custom GPT with a small read-only API you build

**Fit:** You want live answers and have a developer plus a way to host the service securely.

**Effort:** Days to weeks, depending on endpoints and authentication.

### Private model plus Netray or another partner

**Fit:** Controlled data, no cloud allowed, or you want one assistant across ERP and documents.

**Effort:** Scoped pilot, then rollout; hardware needed.

## Pitfalls

- Uploading full database dumps when a masked report would do.
- Trusting numbers from an old export as if they were live.
- Exposing the database directly to the internet to make the action work.
- Letting a custom GPT guess when an endpoint returns no rows, which produces confident but invented answers.
- Forgetting that pasted customer drawings may carry contractual or regulatory restrictions.

## Faq

### Does Infor VISUAL have a built-in ChatGPT integration?

**Answer:** Not that I would assume. Infor offers its own AI capabilities in some products, but a direct ChatGPT connection to a VISUAL install is normally something you build with an exported file or a small API in front of the database.

### Can ChatGPT connect straight to my SQL Server?

**Answer:** Not directly in a safe way. Custom GPT actions call HTTPS endpoints, so you put a narrow service between ChatGPT and the database. Exposing SQL Server itself to the internet is a serious risk and is not recommended.

### Is it safe to paste VISUAL data into ChatGPT?

**Answer:** It depends on the plan, your data and your policies. Business and enterprise plans have different data controls than personal accounts. Customer drawings, controlled technical data and pricing deserve a conservative approach.

### When is a private model better?

**Answer:** When data must stay in the plant, when a contract or regulation restricts third-party processing, or when you want predictable costs at high volume. Quality for structured lookups is often adequate with current open-weight models.

### Can ChatGPT update records in VISUAL?

**Answer:** Technically a service could be built to do so, but it is a poor idea from a chat window. Prefer a proposal-and-approve flow through the supported toolkit so every change has an owner and a record.

## Search terms

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