Text Data Collection
Small, usable datasets from approved sources.
- Collection plan and source rules
- Cleaning, filtering and deduplication
- CSV, JSON or spreadsheet delivery
Boutique language data studio
Better text data for multilingual apps, platforms, and AI tools.
LinguoData helps with collecting, writing, labeling, checking, and cleaning text data in different languages — including safety review for harmful, offensive, or risky content.
Services
Practical services for text-data projects.
Data Generation & Prompt Writing
Original examples when existing data is not enough.
- Prompts, queries and user utterances
- Tone variants and edge cases
- Multilingual versions for testing
Annotation & Dataset Review
Labels, guidelines and checks that make text data easier to use.
- Intent, sentiment, relevance or quality labels
- Simple annotation guidelines
- Model-output or dataset quality review
Safety Review & Moderation Data
Language resources for harmful, offensive or risky content.
- Profanity and abuse lexicons with notes
- Toxic, non-toxic and ambiguous examples
- False-positive checks and moderation guidance
Proof of method
Proof of method: Ukrainian Twitter corpus.
The Ukrainian Twitter corpus project shows a practical workflow for language-data work: collect text, filter noise, document choices and prepare data for NLP tasks. The same method supports language safety resources, where context matters as much as keywords.
View the Ukrainian Twitter corpus →About LinguoData
Small studio, practical language work.
LinguoData helps teams turn messy multilingual text into clean, usable language data.
The studio brings 5+ years of applied Natural Language Processing experience across AI language quality, multilingual QA, corpus work, and toxic-text resources, including AI language work on assignment for Google.
Core language strengths include Ukrainian, Russian, English, and French, with other languages considered depending on the project.
Best fit
Best for smaller text-data tasks.
LinguoData is best suited for small-to-medium datasets, multilingual review, annotation design, safety resources, synthetic data cleanup and evaluation batches.
- Apps or platforms with messy user text
- Teams testing an annotation or review workflow
- Chatbot, search, moderation or localization projects
- Data vendors that need language review support
Start here
Send the messy language problem.
Describe what kind of text data you have and what you need it to become.