Your prompt
“Create a six-page summer home catalog with these products. Use warm colors, a minimal layout, and prices in USD. Put the Arc chair on the cover.”
Describe the catalog you need, then paste a product list, upload a spreadsheet, or share a collection link. AI turns your brief and product details into a first draft you can edit.
“Create a six-page summer home catalog with these products. Use warm colors, a minimal layout, and prices in USD. Put the Arc chair on the cover.”
Review the pages, replace products, adjust prices, and make it yours.
Use a brand template, reuse a past catalog, or ask AI to suggest a layout. Supply product details or connect a source for images, prices, and links; missing details are flagged for review.
Try the sample editorIllustrative workflow. Live generation and product imports aren’t connected in this preview.
Published examples from other brands
Interactive catalogs can connect inspiration to product discovery. Published customer examples show why brands test the channel—and why the comparison behind each number matters.
Capitol Lighting
+22%Catalog-engaged shoppers compared with website-only shoppers.
Publitas reports this comparison for the US lighting retailer after introducing digital catalogs. It describes basket value, not a 22% increase in total sales.
Publitas customer caseMoMA Store
+40–308%Visitors who clicked through from the catalog compared with visitors from other channels.
Reported in a Publitas customer interview. Catalog visitors may already have been more ready to buy, so the comparison does not isolate the catalog’s effect.
Publitas customer interviewPublished by another platform about other brands. These are not our customer results or a forecast. Traffic, products, and campaign conditions differ; the pages do not report a test that isolates the catalog’s effect on sales.
Explore how to measure and improve your editionEstimate the workload for your own catalog. Change the assumptions to compare manual production with a workflow that reuses product data and a brand template.
Repeat-edition estimate
80% less time
6h 30m saved · 65% less time
A model to discuss, not a delivery commitment or measured customer result.
Illustrative planning assumptions, not measured Catalogues AI performance. The example assumes usable product data and a reusable template. Replace the inputs with your own workload; actual generation speed, data cleanup, revisions, and setup time need to be measured in a pilot.
Manual minutes = products × manual minutes per product. Repeat-edition minutes = products × review minutes per product + the per-edition prep/draft allowance. First-edition minutes add the one-time setup allowance. Savings are measured against the entered manual workload; a slower scenario is shown as extra time. The model excludes a separate manual setup allowance and any work not entered above. Times are rounded for display.
The illustrative scenario is ready. Change the assumptions to update it.
The browser demos require no application installation. Production onboarding still needs product-data checks, template approval, and any required connections. We have not established a production setup-time benchmark or a zero-setup promise.
Confirm product fields, image quality, prices, links, and permissions. A clean feed or spreadsheet can reduce preparation work.
Review the layout and map products into it. Rebuilding a past PDF or creating a new template adds work to the first edition.
Store events, product feeds, and publishing requirements depend on the project. Later editions reuse approved mappings and templates, with a content review each time.
Yes—that is the intended workflow. Describe the catalog in plain language and paste a list of products. Choose a template or ask AI to suggest a layout, then edit the generated draft. Supply product details or connect a source for images, prices, and links; anything missing should be flagged for review. The current website demonstrates editing with sample products; live generation and imports are still in development.
Use the planning calculator above to enter your product count, manual workload, review time, per-edition allowance, and first-project setup. It is a scenario model, not a measured Catalogues AI benchmark. We need a pilot with your data and template to establish actual time savings.
The browser demos require no application installation. Production setup includes data checks, template approval, and any connections your project needs. We confirm the scope before committing to a timeline; we do not promise zero setup. Editing an IDML source in Adobe InDesign requires InDesign.
No. The figures are linked, vendor-published examples from other brands. They compare catalog-engaged traffic with other visitors and do not prove that the catalog alone caused extra sales. Catalogues AI does not yet have measured customer uplift results.
Yes. A previous PDF is a useful starting point for your brand’s layout and design. We’ll review what can be reused as a template and what needs to be rebuilt. You keep approval of the final result.
No. We can start the conversation with a website, a product spreadsheet, a feed, or an existing PDF. The right approach depends on how your products, images, and prices are organized. We’ll work that out with your team.
Yes. AI generates the first layout, and your team reviews the products, content, and design. For your design team, the InDesign handoff is an editable IDML file with text, images, styles, and page layouts.