# Swiggy Image Localization Customer Story | Vitra.ai

> See how Swiggy used Vitra.ai image translation to prepare multilingual creative while preserving layout, typography, and review control.

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![Swiggy](https://www.vitra.ai/icons/home/swiggy-logo.svg)

Customer story

# How Swiggy localized image creative with Vitra.ai

Swiggy used Vitra.ai image translation to turn source creative into multilingual versions while keeping the visual layout intact. The workflow brought translation, terminology, design preservation, and human review into one process.

[Contact Sales→](https://sales.vitra.ai/meetings/akash-nidhi-p-s)

![Swiggy multilingual image localization workflow](https://www.vitra.ai/icons/home/swiggy-analytics.svg)

## Company Overview

Swiggy is an Indian food-ordering and delivery platform serving customers across a linguistically diverse market. Its campaign and customer-facing creative often needs more than a translated text file: every regional version must still look like the approved source design.

![Swiggy company overview for the Vitra.ai case study](https://www.vitra.ai/icons/case-study/overview.png)

### Industry

Online Food Ordering

### Content

Campaign and image creative

### Workflow

Image translation and review

![Swiggy logo](https://www.vitra.ai/icons/home/swiggy-logo.svg)

## The Challenge

Text inside campaign images cannot be translated in isolation. Longer words can break the layout, fonts may not support the target script, and copy-and-paste handoffs make it hard to know which version was reviewed. Swiggy needed a way to prepare language variants without rebuilding every creative by hand.

## The solution: image translation inside the creative workflow

Vitra.ai extracted the translatable text from source images, applied the selected language and terminology, and placed the translated copy back into the design. Layout, typography, and visual hierarchy remained part of the job, so the team reviewed a finished creative rather than a detached translation table.

## Implementation

The team started with approved source creative, selected the target languages, and used shared terminology for product and campaign language. Vitra.ai generated editable language versions for review, allowing linguists and creative owners to correct copy or placement before an asset was approved.

## What changed in the workflow

The work moved from separate translation and design handoffs to one traceable production flow:

1

Translated copy stayed with the design

Reviewers could judge the words in their real visual context instead of approving text in a spreadsheet.

2

Layouts remained editable

Creative teams retained control over typography, placement, and final adjustments for each script and format.

3

Terminology became reusable

Approved campaign and product language could be carried into later assets instead of being translated from scratch.

4

People approved the final version

AI handled extraction, translation, and layout work; language and creative owners decided what was ready to publish.

## Where the workflow goes next

The same operating model now sits inside Vitra Universe: one brief and shared memory can feed image creation, image translation, personalization, video, websites, app content, quality checks, and publishing. Teams can expand the workflow when the next campaign needs more formats without replacing the approved context.

## The practical lesson

Creative localization works best when translation is not separated from design. Keeping the source asset, terminology, layout, review, and approved variants in one workflow gives every contributor the context needed to make a good decision.