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AI Data Companies · Machine Translation

Machine Translation Data for AI Data Companies

Data vendors and labelling platforms that win Indian-language work and need a delivery partner on the ground who works to their spec and under their brand. Training and evaluating translation between English and Indian languages, and between Indian languages.

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Abstract visualisation of translation between two Indian languages — Machine Translation Data for AI Data Companies
Buyer
AI Data Companies
Use case
Machine Translation
Metric
Human adequacy and fluency scores
01

Where the two meet

Indian-language capacity is hard to build remotely, especially outside metros That is a machine translation problem, and it is solved by data shaped like this:

  • Sentence-aligned parallel corpora
  • Register-matched to your product
  • Enforced terminology glossary
AI Data Companies · Machine TranslationWhat goes wrongWhat they check before signingIndian-language capacity is hard to build… remotely, especially outside metros…Client QA standards must be met by a subc…ontractor without loss of control…Margins disappear when re-work is needed …after delivery…Will the partner work to our specificatio…n and schema exactly?…Is the partner willing to work white-labe…l under our client relationship?…Is the QA report detailed enough to hand …to our client unchanged?…We quote against the right-hand column, not the pitch.
02

Your evaluation criteria

  • Will the partner work to our specification and schema exactly?
  • Is the partner willing to work white-label under our client relationship?
  • Is the QA report detailed enough to hand to our client unchanged?
Two-speaker conversational recording session in a studio — supporting machine translation data for ai data companies
Two-speaker conversational recording session in a studio
03

Metrics

  • Human adequacy and fluency scores
  • Terminology compliance rate
  • Back-translation divergence
04

Pitfalls

  • Pivoting everything through English
  • Post-edited machine output passed off as human translation
05

Contract points

  • White-label and non-solicitation terms
  • Your schema, your QA thresholds
  • Predictable per-unit pricing

Frequently asked

What does a first engagement look like?

Usually a scoped pilot: one language, an evaluation set plus a first training batch, delivered in three to five weeks, followed by the full programme.

Can you match our existing vendor's schema?

Yes. Working to your schema avoids a conversion pass and keeps deliveries comparable across vendors.

How is provenance documented?

Per-item contributor records and consent mapped to IDs in the manifest.

Send your requirement

Language, volume, metric, deadline.

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