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Data-as-a-service

Training data,built to your spec.

We source, label, review and evaluate the data your models learn from, with native Arabic annotators across 25+ dialects and domain experts in finance, healthcare, logistics and government.

Scope a projectBrowse the data catalogue

Training data, done properly.

Sourced, labelled and checked by people who know the language and the domain, then delivered where it has to stay.

  • Quality

    Labelled at 98% accuracy, with human-in-the-loop checks on every project.

  • Scale

    30M+ data points annotated for 250+ enterprise and government organisations.

  • Arabic depth

    Native annotators across 25+ dialects, with domain experts in finance, healthcare, logistics and government.

  • Kept in region

    Hosted and processed in region: on-premises, hybrid or in the cloud. SOC 2 Type II and ISO 27001.

Supported data types

Every data type, labelled by people.

Text labelling example

Text

Entities, sentiment, moderation and preference labels, in Arabic and English.

What we label

  • Named entities
  • Sentiment
  • Content moderation
  • Ranked model responses

Sample recordIllustrative, not customer data

{
  "text": "افتتح المعرض في دبي يوم الأحد",
  "entities": [
    { "span": "دبي", "type": "LOCATION" },
    { "span": "يوم الأحد", "type": "DATE" }
  ],
  "sentiment": "neutral",
  "reviewed_by": "native annotator"
}
Explore text data

What we do

Four services, one data partner.

Data sourced for your model, not pulled off a shelf.

  • Domain-specific datasets
  • Field collection, in the places the work happens
  • Integration with your enterprise systems
  • Synthetic data in controlled environments
Talk to us about a collection

How a project runs

Every batch makes the next one better.

  1. 01

    Scope

    The model, the data behind it and the rules for labelling it.

  2. 02

    First batch

    Sourced, labelled and checked by a person before it reaches you.

  3. 03

    Review with you

    Your team reviews it. What the review finds goes into the guidelines.

  4. 04

    Scale and deliver

    The full set, delivered into your training run, kept in region.

Review findings feed the guidelines for the next batch.

The people on the line

A factory run by people, not just pipelines.

Data catalogue

Need data that already exists?

Browse ready-made categories by modality and add them to one request.

Browse the data catalogue

FAQ

Questions buyers ask

Something we have not answered? Ask the team.

How is this different from the data catalogue?

The catalogue lists ready-made data categories you can add to a request. Data services is a managed project: we source, label, review and evaluate data to your specification.

How accurate is the labelling?

Text, image, video and audio are labelled at 98% accuracy, with human-in-the-loop quality assurance on every project.

Who does the work?

Native Arabic annotators across 25+ dialects, domain experts in finance, healthcare, logistics and government, and human AI evaluators in biology, medicine, finance, coding and bilingual work.

How does a project start?

With discovery: the problem, the systems it touches and the data behind it. That becomes a roadmap, then a first build phase, a review, a second build phase and sign-off.

Tell us what your model needs to learn.

Share the task, the languages and the volume. We come back with a scope, guidelines and a first batch.

Scope a projectBrowse the data catalogue