# Satvik Jagannath on contextual translation, in conversation with MediaBrief | Vitra.ai

> Satvik Jagannath tells MediaBrief how Vitra.ai makes content creation and translation seamless, and why contextual translation beats word-for-word machine translation.

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# Satvik Jagannath on contextual translation, in conversation with MediaBrief

Media Brief

Satvik Jagannath tells MediaBrief how Vitra.ai makes content creation and translation seamless, and why contextual translation beats word-for-word machine translation.
[Visit Website](https://mediabrief.com/satvik-jagannath-exclusive-vitra-ai)

[Satvik Jagannath](https://www.vitra.ai/author/satvik)
Co-founder and CEO , Vitra.ai
Dec 6, 2022

![Satvik Jagannath on contextual translation, in conversation with MediaBrief](https://www.vitra.ai/static/images/news/5.webp)

Media Brief

Table of contents

[The interview](#the-interview)

[Contextual versus literal translation](#contextual-versus-literal-translation)

[Source](#source)

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[Satvik Jagannath](https://www.vitra.ai/author/satvik)
Co-founder and CEO

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## The interview

In an exclusive interview with MediaBrief in December 2022, co-founder and CEO Satvik Jagannath set out the case for what he calls contextual translation, and filled in some of the company's early history.

On the product, the pitch was consolidation: video, images, text and podcasts translated from one tool, in one click, instead of the back-and-forth of briefing separate vendors per format. On the origin, Jagannath dated the build to mid-2019, before the pandemic, bootstrapped at the start, with a founding goal of translating educational content so that, in the company's phrasing, language would not be a barrier to learning. The name is literal: Vitra stands for Video Translation.

## Contextual versus literal translation

The distinction the interview turns on is the one that still separates the product from generic machine translation. A literal engine maps words. A contextual engine resolves what a sentence is doing before it decides how to say it in the target language, which is what keeps a product disclosure legally equivalent and a piece of marketing copy still persuasive.

That engine is now the shared layer under [video dubbing](https://www.vitra.ai/features/video-dubbing), [image translation](https://www.vitra.ai/features/image-translation) and [website translation](https://www.vitra.ai/features/website-translation), with a [translation memory](https://www.vitra.ai/features/translation-memory) that keeps terminology consistent across all of them.

## Source

- [Media Brief](https://mediabrief.com/satvik-jagannath-exclusive-vitra-ai) — Satvik Jagannath on contextual translation, in conversation with MediaBrief

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