aidataservices.inAI data collection · India

Who we work with

Indian AI Training 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.

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AI team reviewing dataset dashboards — Indian AI Training Data for AI Data Companies
Typical engagement
Overflow and specialist capacity across Indian languages
Languages
14 + Indian English
Model
Direct or white-label
01

The problems that bring teams here

  • Indian-language capacity is hard to build remotely, especially outside metros
  • Client QA standards must be met by a subcontractor without loss of control
  • Margins disappear when re-work is needed after delivery
AI Data CompaniesWhat 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

What you are actually buying

Need 500 hours of Marathi speech from 1,000 speakers? Need 2,000 Hindi speakers? Need natural Hinglish conversations? Need Indian English accents across substrate groups?

Those are specifications, not projects. Send the spec and you get a quote against it. If the spec is not written yet, a 20-minute scoping call produces one.

Field recording session with a rural speaker in India — supporting indian ai training data for ai data companies
Field recording session with a rural speaker in India
03

How teams like yours evaluate a data partner

  • 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?
04

Typical scope

Overflow and specialist capacity across Indian languages, priced per hour or per unit against your spec.

05

Contract and licensing points you will raise

  • White-label and non-solicitation terms
  • Your schema, your QA thresholds
  • Predictable per-unit pricing
06

How the engagement runs

  • You send requirements, or we scope them with you
  • We return a written specification, timeline and fixed quote
  • You approve; recruitment and prompt design begin
  • Sessions run across the studio network with progress reporting
  • QA, packaging and staged delivery against the manifest schema you specified
07

The numbers we hold ourselves to

  • 100% of delivered files pass automated technical QA for SNR, clipping, duration and silence
  • 5-25% of files pass a second native-speaker content review, stratified by city, dialect and transcriber, and escalating to 100% on any batch that fails the agreed threshold
  • Accepted yield runs 85-90% for scripted speech, 60-70% for spontaneous, 55-65% for conversational and 50-60% for telephony
  • Default cohort quotas: 50/50 gender, with age bands at 30% (18-25), 40% (26-40) and 30% (41-60)
  • 48 kHz / 24-bit capture, delivered as 16-bit PCM WAV, with studio sessions held below a -50 dBFS noise floor
  • First response within one working day; a scoped, fixed quote within two to three

These are the figures a delivery is measured against, not aspirations. A batch that misses them is re-recorded at our cost rather than repaired.

Frequently asked

How quickly can you start?

Specification and recruitment usually take one to two weeks; recording starts immediately after. Low-resource languages take longer to field and should be started first in a multi-language programme.

Can you work under our brand?

Yes. White-label delivery is standard for data vendors and platforms who hold the end-client relationship.

Do you handle consent and provenance?

Every participant signs consent covering AI training and downstream model distribution, and consent records map to file and item IDs in the delivered manifest.

What if a batch fails QA?

It is re-collected. The commercial terms cover re-collection rather than partial credit, because a partially usable dataset costs you more than a late one.

Send us your requirement

Language, hours, speakers, demographics, format, deadline. That is enough for a quote.

Request a dataset quote