Text & Documents
Annotate and extract entities in 55+ languages for computer vision and NLP tasks. Power your models with curated human intelligence.
RUN FREE PILOTMultilingual Entity Extraction & Document Processing
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Your data problem
has a human solution.
ML Engineers
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OUR ANNOTATION SERVICES FOR TEXT & DOCUMENT DATA
We provide high-precision annotation for all major natural language processing tasks, document intelligence, and multilingual text datasets in 55+ languages. Our global team can expertly deliver the following annotation services:
Named Entity Recognition
Extract critical data points and entities with precision.
a road trip from DallasLOCATION to MiamiLOCATION
stopping in AtlantaLOCATION along the way.
A Futureproofed Pipeline
We exist for a future where high-performance machine learning models are built on pristine, expertly curated data perfectly running within your infrastructure.
Free Pilot
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Estimate Your Costs for ML projects
1 Pick application field
2 Select annotation method
3 Specify how many objects to label
4 Check the approximate total cost
5 Run free pilot
Why Projects Choose Engai for Data Annotation
Accelerate AI Development
Speed up your model training with perfectly structured, instantly usable data flows designed for seamless integration.
Unmatched Precision
Our stringent multi-level QA protocols and proprietary tooling ensure the highest possible ground-truth accuracy.
Infinite Scalability
Whether you need thousands or millions of data points labeled, our global workforce scales effortlessly to meet your demands.
Safe and secure
Your trust is our foundation. Engai is designed with a deep commitment to data privacy and security. Visit our trust page and security center to learn more.
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Discover how Engai's Data Pipeline and AI Infrastructure platform can make your organization AI-ready:
Automatically discover and map all datasets with contextualized inventory
Effortlessly manage ML lifecycle and address governance gaps
Drastically reduce deployment time by mitigating edge-case risks
Immediately detect and respond to model drift to minimize threat impact
Proactively apply zero-trust protection mechanisms for proprietary data
Live Infrastructure Telemetry
Zero-Trust Dataset Confidentiality
Your requirements and proprietary sample assets are encrypted in transit and never used for public model training.
Frequently Asked Questions
Text labeling (or text tagging) is the essential process of assigning metadata to phrases, sentences, or paragraphs within documents. This ground-truth data allows Natural Language Processing (NLP) models to understand context, identify key entities, and categorize information accurately for AI-driven automation.