We mark up your images and video, saying what each thing is and where, so AI can learn to recognise it.
Explore serviceData & annotation
Teach AI to read, with clearly labelled text.
An AI that reads emails, reviews or contracts learns from examples that people have labelled. We mark up names, topics, intent and mood in text, and pull the key details out of documents into the fields you need. The rules and the tricky cases are written down, so labels stay consistent as the work grows.
What we offer
Text Annotation services.
- 01
Named entity recognition
People, organisations, products, dates, amounts and custom entity types tagged at span level.
- 02
Sentiment and emotion
Polarity, intensity and emotion labels for reviews, support tickets, social posts and survey answers.
- 03
Intent and classification
Messages and queries sorted into intents, topics or categories that match your product's taxonomy.
- 04
Relation extraction
Links between entities, such as who works where or which clause refers to which party.
- 05
Document classification and extraction
Invoices, contracts, forms and reports classified, with key fields captured into a structured schema.
- 06
PII detection and redaction
Personal data identified and masked or removed so text can be used safely for training and analysis.
- 07
Multilingual text
Annotation across languages by reviewers fluent in each one, working from a shared set of guidelines.
How we work
From guidelines to delivered data.
AI takes the first pass, trained people review it, and quality is checked before delivery.
- 01
Scope
We agree label definitions, edge cases, formats and quality targets with you.
- 02
Pilot
A small batch tests the guidelines before any volume work starts.
- 03
Annotate
Trained annotators label to the agreed guidelines, with tooling to match.
- 04
Review
Multi-stage quality review against the specification, with feedback loops.
- 05
Deliver
Data in your format, with notes on what was checked, then we iterate.
Where it helps
Typical projects.
The kinds of work this service usually supports.
Support automation
Training models that route tickets, detect urgency and suggest replies, using labelled support history.
Search and retrieval
Labelling queries and documents so search and retrieval systems return more relevant results.
Document processing
Extracting parties, dates, obligations and clauses so legal and finance teams can search and compare documents.
Voice of the customer
Turning reviews, surveys and social posts into sentiment and topic data that product teams can act on.
Details
Output formats
- JSONL
- CoNLL (BIO tags)
- spaCy training format
- Hugging Face datasets
- Label Studio JSON
- CSV
- Custom schemas
Questions
Which languages can you annotate?
We staff each project with reviewers fluent in the languages you need, and confirm coverage during scoping before any work starts.
Can you handle confidential documents?
Yes. We work under NDA, agree access controls and retention rules with you, and can redact personal data before wider annotation begins.
Do you use pre-labelling?
Where it helps, we use models to suggest labels and reviewers correct them. You decide whether pre-labelling is used, and labels are still reviewed by people.
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Idea → Architecture → Prototype → Production → Scale
Talk to us about Text Annotation.
Tell us what you're trying to build, test, automate or improve. We'll tell you honestly where we can make a real difference, and where we can't.