How to Connect Modelry to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Modelry

You have an Excel workbook full of SKUs, spec sheets, and campaign schedules. Modelry holds the 3D models, the AR-ready assets, and the modeling request queue for all of them. Getting data between those two places requires you to open the Modelry dashboard, navigate workspace by workspace, export what you can, and paste it somewhere useful — then do it again when anything changes.

Modelry is good at managing 3D product visualization workflows at scale. But the data you need for planning and reporting lives in workbooks, and Modelry does not speak Excel natively. The usual move is a CSV export from Modelry, a round-trip through a text editor to fix encoding, and thirty minutes of column cleanup before the workbook is actually usable.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default for most teams. You open the Modelry dashboard, export what you can to CSV, open the CSV in Excel, copy the columns you actually need, and paste them into your working workbook — renaming headers, fixing date formats, and dropping the columns Modelry included that you didn't ask for.

For a one-time snapshot this is tolerable. The problem arrives on week three, when you are doing this again for the same 120 SKUs because the campaign moved, or because a stakeholder wants a fresh status report, or because the product team added 15 new items and you are not sure which ones are in Modelry yet. The tedium is not in the first export. It is in the seventh.

Method 2: Power Automate

Power Automate has Modelry connector options. You can wire up a flow — triggered on a new modeling request, a status change, a new product — and push that event into a row in your Excel workbook automatically.

A quick check before you go further: do you know what an HTTP action is in Power Automate? Do you know how to parse a JSON response and map nested properties to workbook columns? Do you know what a connection reference is and what breaks when you move a flow between environments? If those concepts are not already in your toolkit, this path is going to cost you more time than the CSV export. You are better off at Method 3 or 4.

If you are still here: the flow itself is achievable. You authenticate both ends, pick a trigger in Modelry, configure the response parsing, map fields to your worksheet columns, and deploy. It works.

But a trigger-per-event flow is not the same as a bulk pull.

If you need all 120 products at once — not just the ones that changed this week — you are looking at a scheduled recurrence flow with a paginated API loop, which is a different beast entirely and tends to require premium connector access.

You probably just need the product list out of Modelry and into your workbook. You probably have no idea how to build a paginated recurrence flow in Power Automate — and you shouldn't need to. So the task lands on whoever on your team builds automations, and now you're waiting for a reply from someone who has four other things queued ahead of yours.

Even once it's built: the moment you need to filter by workspace, join against a second worksheet, or aggregate completion percentages across jobs, you have left Power Automate's native capabilities behind.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable workbook ↔ Modelry workflows was a category of add-ons that let you configure column mappings and saved templates. You picked your product list range, you tagged your status fields, you saved a config, you ran it.

That was a real step up from copy-paste. Output was consistent, configs were reusable, the team didn't have to redo formatting every run.

But you were still responsible for the template design, the field mapping, the schedule, the conditional logic about which products to include, the renaming of columns between what Modelry called them and what your workbook used. The tool got the data through, but the thinking was still on you. And the moment Modelry changed a field name or you restructured your workspace, your config broke until someone went back in and fixed it.

This is the previous generation. It worked, but it asked a lot of the operator.

The Easy Way: Using SheetXAI in Excel

There is a different way entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads your workbook, understands what you are looking at, and through its built-in Modelry integration it can push to or pull from Modelry for you. No template configuration, no automation glue, no CSV wrangling. You just ask.

Example 1: Export your full product catalog into the workbook

List all products in our Modelry workspace and write product name, ID, and current modeling status into this sheet — one row per product, starting at row 2

SheetXAI hits the Modelry API, walks the product list, and populates columns A through C with name, ID, and status. If a product has no model yet it writes "not started." If it has one in progress it writes the current stage.

Example 2: Submit a batch of modeling orders from the workbook

For each row in my sheet where column D is "approved," submit a Modelry 3D modeling order using the product ID in column A and the spec notes in column C, then write the returned order ID into column E

The conditional logic — only approved rows, not the whole worksheet — runs inside the single prompt. SheetXAI reads the column, filters to the right rows, places each order, and writes the result back without you touching a row individually.

Try It

Get the 7-day free trial of SheetXAI and open any Excel workbook with your Modelry product list, modeling queue, or SKU tracker, then ask it to do one of the tasks above. The Modelry integration is included in every SheetXAI plan.