Powering decisions that win
The brands your competitors are watching
Eight data types, collected to your requirements
Text
Native writing across 100+ languages, structured or free-form.
Bespoke text, built to your spec
We collect the text your model needs in the languages and fields it will work in.
Why do language models fail?
Scraped, English-heavy text trains a model that breaks on native phrasing, real domains, and other languages.
Reads well on familiar phrasing. Breaks on native idioms, domain languages, and low-resource languages.
Holds up in the languages and registers your users actually write in.
What does scraped and synthetic text miss?
Your model trains on dataset collected from contributor network by Rwazi.
What does a text sample look like?
Your pack arrives as text matched to your fields and languages. Every record carries demographic metadata and a consistent naming convention, dropped straight into your cloud.
Native multilingual writing, across 100+ languages.
Request accessDomain documents across legal, medical, and technical fields.
Request accessStructured records and forms for extraction.
Request accessHuman-written prompts and responses for fine-tuning and detection.
Request accessWhat we capture to your spec
Two ways to collect your text
Pick the one your model needs, or use both.
Native authoring
For models that must hold up across languages. Real native writing in the languages and registers your users speak.
Targeted collection
For models that need precision. Domain documents and structured records collected to a tight brief.
Real-world text in 100+ languages
Most text sets lean on English and a few big languages, so models break elsewhere. Rwazi collects natively written text from 190+ countries and 100+ languages.
- 190+ countries
- 100+ languages
- native and translated
- structured and unstructured
- domain and general
What sets Rwazi text data apart?
What are teams training with Rwazi text datasets?
LLM training and fine-tuning
Models lean on scraped, English-heavy text and break everywhere else.
Natively written text across 100+ languages.
Text datasets for the task you are training
We build text and NLP datasets for machine learning, scoped to your task.
From your spec to your cloud, in four steps
Run it as a one-off project or a recurring refresh, weekly or monthly.
How Rwazi compares to other providers
The same data, captured in the real world. Here is how that stacks up against the alternatives.
Rwazi builds real-world AI datasets.
Our 5M+ consumer network captures data in real environments across 190+ countries, so your models train on what your users actually produce.
Every record earns its place in your dataset
You write the pass-or-reject criteria. People review each record against those criteria and log who wrote it, where, and when. We report what passed before the dataset reaches you.
Tell us your scope or book a live demo
Contact the Rwazi AI datasets team
Book A Live Demo
Questions teams ask before they buy
What is LLM training data?+
Text used to train and fine-tune language models, from native writing and domain documents to human prompts and responses. We collect it to your spec across 190+ countries and 100+ languages.
What languages can you collect?+
We collect in any language our contributors speak, across 100+ languages and 190+ countries. English, French, Spanish, Chinese, and Hindi are the most widely available.
Do you offer structured and unstructured text?+
Yes. We collect structured records and free-form writing, to whichever mix your model needs.
Can you collect domain-specific text?+
Yes. We collect legal, medical, technical, financial, and consumer writing to your brief.
Does it include sentiment or labeling?+
The text itself is the deliverable. Sentiment, labeling, classification, and post-processing come as add-ons.
Do you have human-written data for AI-versus-human detection?+
Yes. Verified human-written text across domains and languages, giving your detector a clean human reference.
What formats and delivery do you support?+
We deliver JSON, CSV, and TXT to your S3, Azure Blob Storage, GCS, or via SFTP.
How is it priced?+
We quote per project. The drivers are volume, languages, domains, exclusive versus licensed, and any add-ons. Send your brief and we will price it.
How do you handle consent and ownership?+
Every contributor writes under explicit consent, and Rwazi owns all the text. You license the set or take it outright, and provenance travels with each record.
How does this compare to scraped or synthetic text?+
Scraped and synthetic text carries licensing risk and misses native phrasing. Real contributors write to your spec under explicit consent, and Rwazi owns it from the point of collection.
What does a delivery look like?+
A quality-checked set in the format you choose, named to a consistent convention, with age, gender, and location tagged on every record, dropped into your cloud.
Where can I buy multilingual text datasets?+
Tell us the languages and fields you need. We scope a bespoke multilingual text dataset, write it to spec, and license it to you or hand over ownership.