Data labeling services that keep every class consistent Clear classes, a written guide, and a person on every unclear item
Data tagging services for vision, language, and speech Damco labels the data your model learns from, to one written guide
How our data labeling process works From a class list to labeled batches your pipeline can read
- Week 1Define the classesWe agree each class with examples, counter-examples, and a catch-all class.
- Week 2Label a pilotYou review a pilot, and we tighten the guide where labels disagreed.
- From week 3Label at volumeAgents tag every item, and reviewers decide those below the confidence bar.
- Every batchAudit and deliverA second reviewer checks a random sample before the batch owner signs.
When to outsource data labeling And when to keep labeling inside your own team
A good fit when
- Your class list is stable, and you need thousands of items labeled a week
- Your engineers are labeling data instead of improving the model
- You want agent pre-labels, but someone has to check them
Look elsewhere when
- Only a licensed specialist may label your data, such as a radiologist
- You need a few hundred labels once, and a labeling tool will do
- Your classes change every day while the product is still being defined
Data labeling for machine learning in detail The labels we add, the industries we serve, and how we keep them accurate
Data labeling for computer vision
Vision models learn to detect and sort objects from labeled images and video. We tag whole images with a class, such as damaged or undamaged, and tag the objects inside them when the model has to find them.
When a project needs boxes, masks, or points drawn, the work follows our image annotation and video annotation guides.
Data labeling for natural language processing
Language models need text tagged by intent, topic, sentiment, and part of speech. We write examples for each tag, so two reviewers reading “cancel my plan” and “stop the subscription” tag both as the same intent.
Audio transcription for speech recognition
Speech models learn from audio written down word for word. We transcribe recordings, mark who is speaking, and tag background noise, hesitations, and words the speaker corrected.
Accents, crosstalk, and noisy lines go to a person by default.
Automated data labeling with LLMs
Large language models now suggest good first labels for most text and many images. We use them for the first pass, measure them against a reviewed sample, and set the confidence bar below which a person decides.
Every correction a reviewer makes goes back as an example, so fewer items need a person next time.
Data labeling services for every industry
We label data for teams in autonomous vehicles, agriculture, retail and ecommerce, wildlife research, security and surveillance, healthcare, banking, insurance, manufacturing, logistics, and robotics.
A crop disease, a claim photo, and an empty shelf each need their own classes, so each project gets its own guide.
How we keep data labels accurate
Accuracy comes from a guide with examples, a second reviewer on a random sample, and agreement scores that show where people disagree. When reviewers disagree, we fix the guide, not just the label.
Your team sees the scores with every batch, so you know how far to trust the labels before you train on them.
Questions about data labeling services What teams ask before they outsource data labeling
How do you ensure accuracy in the data labeling process?
We start from a written guide built around your model's use case, with examples for each class. A second reviewer audits a random sample of every batch, and agreement scores show where labels drift. When they drift, we fix the guide and relabel the items it affected.
What tools and technologies do you use for data tagging?
We work in your labeling platform if you have one, or in an open-source tool such as CVAT or Label Studio. Agents built on language and vision models draw the first labels, and reviewers correct them. We export in the format your pipeline reads, such as JSON, CSV, or COCO.
What is the turnaround time of your data labeling services?
It depends on the volume, the number of classes, and how many items need a person. Smaller projects take days and larger ones take weeks. We agree a date for every batch before it starts.
Is my data safe and confidential when you label it?
We agree with you where the data is stored, who may see it, and when it's deleted. Access is limited to the people on your batch, each under a confidentiality agreement. If your data can't leave your systems, we work out access with your IT team.
Can you label data with LLMs and keep quality?
Yes, for many tasks. We measure the model's labels against a reviewed sample first, and items below the agreed confidence go to a person. You see both numbers with each batch.
Send us your class list and a sample
We'll reply with how we'd run the pilot and the price per label.