Your model is only as good as the data behind it.

AI training data is the labelled material a model learns from, such as annotated images, transcribed audio or ranked text responses. Its quality sets the ceiling on how well a model can ever perform, which is why most serious programmes spend more on data than on compute.

An AI data annotation company marks up raw data so a machine learning model can learn from it, applying a defined set of rules consistently at very large volume. The work includes designing those rules, training and certifying annotators, then running the quality assurance that keeps labelling consistent across millions of items.

Specialist data operations providers do, and Corpshore AI is one of them. RLHF means reinforcement learning from human feedback, where trained people rank or correct model outputs so the model learns what a good answer looks like.

More than 35, including low resource African, Central Asian and Southeast Asian languages that general vendors often decline. Native speakers work in the region the language is spoken, rather than the work being approximated from elsewhere.

Across more than 18 countries in six regions: Africa, Asia Pacific, Central Asia and Türkiye, Europe, Latin America and the Caribbean, plus North America and the Gulf. Programmes can be delivered from one hub or split across several for language coverage or time zone reasons.

Through certification before an annotator touches production work, multiple review passes on sampled output, then continuous measurement against a gold set. Quality is reported as a number you can see rather than claimed as a standard.

Data collection creates new raw material, such as recording speech or capturing video that did not exist before. Data annotation adds the labels that make existing material learnable. Most programmes need both, and doing them together keeps the labels aligned to how the data was captured.

Yes. We record scripted and spontaneous speech in languages with little or no existing corpus, balanced across accents, ages and recording environments. It arrives with verbatim transcripts and speaker metadata.

A scope call happens within days and a paid pilot typically runs inside three weeks. Scaling a pilot team into a full programme usually takes a further four to six weeks, depending on how many languages and how much certification the work needs.

Book a scope call or email info@corpshore.ai with what you are building and roughly how much data you need. Pricing depends on modality, language, quality bar and volume, so an honest number needs a short conversation rather than a rate card.