Prompts and prompt sets
Prompts for multilingual models and assistants, translated so each one asks for the same thing in every language.
For multilingual assistants and prompt testing
Our tool: Translation Free sample of prompt translation
Multilingual data for AI teams
Human-verified translation and localization for AI teams
Translation and localization, so your prompts, interface text and datasets work in the languages and markets you're aiming at. People verify every output, across widely spoken and low-resource languages, with deep coverage of Indian languages. The work runs in our own Translation tool.
- en Hi {name}, your order ships on {date}.
- hi नमस्ते {name}, आपका ऑर्डर {date} को भेजा जाएगा।
- es Hola, {name}: tu pedido se envía el {date}.
placeholders kept formal register terms consistent
✓ linguistic review done Translation tool
The short answer
What is translation and localization for AI?
Translation and localization for AI turns prompts, interface text and training data into other languages, so a model or product works for people in those markets. Translation carries the meaning across. Localization adjusts what else a market expects, like dates, names, formality and tone.
For AI data the rules are stricter than for documents. A labeled sentence has to keep its label, placeholders have to come through untouched, and the same term has to be translated the same way every time, or the dataset drifts.
Machine translation can produce a first draft. People who know the language verify it, and a linguistic and cultural review sits on top. Our text data page follows one message from how people wrote it to its translation.
Translation at IndecalAI
- What
- Prompts and prompt sets, UI copy, and whole training datasets.
- Languages
- Languages worldwide, from widely spoken to low-resource, with deep coverage of Indian languages.
- Review
- Human-verified, with a linguistic and cultural review on top of any machine draft.
- Tools
- Our own Translation tool, built for multilingual conversion workflows.
- People
- Translators and reviewers from a network of 30,000+ people worldwide.
- Quality
- A final review before delivery.
- Your data
- NDA first, used only for the agreed scope, returned or deleted when you ask.
- Contact
- One named contact who replies within one business day.
- First step
- A small free sample before you commit.
- Company
- Based in Ahmedabad, India, since 2021, with 150+ projects delivered.
What we translate
Six kinds of translation work for AI
Prompts and prompt sets for multilingual models and assistants. Interface text, localized for the markets you're targeting. Whole datasets carried into new languages. A linguistic and cultural review sits on top of any machine draft, and the work runs in our own Translation tool.
Interface text
UI copy localized for the markets you're targeting, checked so the longer languages still fit the space they get.
For apps and products launching in new markets
Our tool: Translation Free sample of UI localization
Whole datasets
Training data translated or localized into new languages, with every label carried across and checked.
For training a model in a new language
Our tool: Translation Free sample of dataset translation
Placeholders and terms
Variables and placeholders come through untouched, and the same term is translated the same way every time it appears.
For templates, notifications and bot replies
Our tool: Translation Free sample of template translation
Localization for the market
Dates, names, honorifics and level of formality change with the market, so the text reads as if it was written there.
For support bots and assistants that sound local
Our tool: Translation Free sample of localization
Low-resource languages
Where there's little written material online, a machine draft needs heavier human correction, and native speakers matter even more.
For reaching languages the big models handle badly
Our tool: Translation Free sample of low-resource language translation
Where it's used
What translated data does for a model
Common jobs for translation and localization in AI work, and the part of this page behind each one. They're examples of the work, not a client list.
Multilingual assistants
The same prompts in every language your assistant supports, so it gets tested and tuned on equal terms.
Launching in a new market
Interface text that fits the screen and reads naturally, not like a word-for-word conversion.
Training data in a new language
An existing labeled dataset carried into a new language with its labels intact.
Support bots that sound right
Replies with the right level of formality for the market, so the bot doesn't sound rude or oddly stiff.
Languages with little data
Material in low-resource languages, where native speakers do most of the work a machine can't.
Testing in every language
Translated test sets, so your model gets checked in each language it's meant to handle.
Why AI data is different
Translating data isn't like translating documents
A prompt or a labeled sentence has to keep its meaning and its label. Placeholders and variables have to come through untouched. The same term has to be translated the same way every time it appears, or the dataset drifts.
Localization goes a step further. Dates, names, honorifics and level of formality all change with the market. Hindi, for example, has separate forms of "you" for formal and informal speech, and a customer support bot that picks the wrong one sounds either rude or oddly stiff.
Before translation starts
Settle these first
Four decisions made up front keep a translated dataset consistent from the first item to the last.
Key terms
One agreed translation for every product name, technical term and label, kept in a list the whole team works from.
Level of formality
Formal or informal, and which form of "you". It changes by market and by product, so it's decided once.
Placeholders
Which variables, tags and codes must come through untouched, and where they can move in the sentence.
Script and spelling
Many Indian languages have their own scripts, but people often type them in Latin letters on a phone. Decide which your product expects, or whether it needs both.
How it works
From your material to reviewed translations
One person owns your project and fields the questions. Translation work moves through these steps.
Material and market
You share the material and tell us the market you're aiming at.
NDA first
The NDA is signed before any of your data moves.
Terms and rules
We settle key terms, the level of formality and how placeholders are handled.
Free sample
We translate a small sample free, so you can check it before you commit.
Translation
Translators and reviewers work in our Translation tool, with a linguistic and cultural review on top.
Final review and delivery
A final review runs before anything is delivered.
Languages
Widely spoken and low-resource languages alike
We work in languages from all over the world and go deep on Indian ones, well past Hindi and English. Our page on Indian language data says more about scripts and spelling.
Glossary
Translation terms you'll run into
The words that come up when you plan a translation or localization project, and what each one means.
- Localization
- Adapting text for a market beyond the words: dates, units, names, formality and tone.
- Machine translation post-editing
- A person correcting a machine's draft until it's right. Also called MTPE.
- Low-resource language
- A language with little written material online, where machine translation tends to be weakest.
- Placeholder
- A variable like {name} or {date} in a string, filled in by software later. It has to survive translation untouched.
- Term base
- The agreed list of key terms and their translations, so every translator uses the same words.
- Register
- How formal the language is. Many languages mark it in grammar, like the formal and informal forms of "you".
- Transliteration
- Writing a language in another script, like Hindi in Latin letters. The words stay the same.
- Text expansion
- Translated text often runs longer than the source, so interface text has to be checked for fit.
Related work
What surrounds a translation project
One team can collect data in a new language, translate what you have and check your model in each one. You can also compare all eight services.
Data collection
New data collected in the language, instead of translated into it.
Conversational AI data
Dialogue recorded by native speakers in each market.
Transcription
Speech in any language turned into reviewed text first.
Data annotation and labeling
Labels added or checked in the new language.
Data and model evaluation
Your model checked in every language it supports.
FAQ
Questions about translation and localization
Short answers about this service. The services FAQ covers the other services and how they fit together.
What is the difference between translation and localization?
Translation carries the meaning into another language. Localization adjusts everything else a market expects: dates, names, honorifics, level of formality and tone. A support bot needs both to sound right.
Which languages do you translate?
Languages from all over the world, from widely spoken to low-resource, with deep coverage of Indian languages.
Do you use machine translation?
Machine translation can be a first draft. People verify it, and a linguistic and cultural review sits on top.
How do you keep labels and placeholders intact?
We settle key terms, the level of formality and how placeholders are handled before translation starts. Translators follow those rules, and the review checks them before delivery.
Can you translate into low-resource languages?
Yes. We work in widely spoken and low-resource languages alike. In a low-resource language a machine draft needs heavier human correction, and native speakers matter even more.
Can you localize interface text as well as datasets?
Yes. We localize prompts, UI copy and training data for target markets.
What do you need from us to start?
The material, the source and target languages, the market you're aiming at and a rough volume. A list of key terms helps if you have one.
Can we try a small sample first?
Yes. Send a short brief and we'll translate a small sample free before you commit.
Does our data stay private?
Yes. The NDA is signed before any data moves, we use it only for the scope we agreed, and only the people working on your project can get to it. It's returned or deleted when you ask.
Start with a free sample
Pick what needs translating, add the languages and roughly how much there is, and send it. We'll translate a small sample free before you commit.
- Your named contact replies within one business day.
- We sign an NDA before any data changes hands.
- We translate your free sample, then agree the full scope.
This opens your email app with the brief filled in. Nothing is sent until you press send. You can also use the contact page.