Rows of annotators working quietly at monitors in a night-shift office in Manila, desk lamps glowing, screens too soft to read

/Offshore · Data Annotation

Offshore data annotation that runs on written guidelines.

Offshore data annotation places the team that labels your training data in a distant country, usually at the lowest cost of the three delivery models and on a different working day. We run offshore annotation teams in the Philippines, India and Egypt through partner centers we select and manage. This guide covers which tasks suit the model, how overnight queues and handoffs run, how quality is checked without daily calls, how to keep data safe and when nearshore is the better choice. For the service itself, see our data annotation outsourcing page.

What offshore data annotation is

An offshore annotation team works from a country many hours away, inside your labeling platform, on guidelines you’ve written down. Each of the three locations brings something different.

The Philippines is on UTC+8 with no daylight saving, 12 or 13 hours ahead of US Eastern, and has a large English-speaking back-office workforce. India is on UTC+5:30, also with a large English-speaking workforce. Egypt is on UTC+2, or UTC+3 in summer, and adds Arabic alongside English.

The team usually works its own daytime, which is your night. That gives you very few shared hours with your ML team, so the guideline has to carry the answers a call would otherwise provide.

Source: IANA Time Zone Database

What offshore does well

The first benefit is cost. Offshore is the lowest-cost of the three models, which matters most on large datasets where every label is paid for.

The second is time. A team in Manila or Bangalore labels while you sleep, so the batch you queued at the end of your day is done and reviewed when your engineers start the next morning. With teams in more than one country, the queue can move almost around the clock.

The third is scale. Large workforces make it practical to add annotators for a new dataset or a retraining push, then step back down once it’s done.

Annotation tasks that suit offshore

Offshore works best where the right answer is already written down. The clearer the guideline, the better the fit.

Task	Offshore fit	Why
Image classification and bounding boxes	Strong	Clear visual rules, high volume and easy to sample
Polygons and segmentation	Strong	Slow, precise work that rewards a large, trained team
Video object tracking	Strong	Long, repetitive frame-by-frame work that runs well overnight
English transcription	Strong	Fixed style guide; uncertain audio gets flagged, not guessed
Content moderation queues	Good	Works with a stable policy and the wellbeing measures below
LLM evaluation with a fixed rubric	Moderate	Fine with a clear rubric; open-ended judgment needs calibration
Spanish or code-switched data	Weak	Native Spanish speakers in nearshore do this better

How overnight queues and handoffs work

Offshore annotation runs on handoffs, not conversations. Here’s a typical cycle for a US team working with annotators in the Philippines.

End of your day Your ML team loads the next batch, answers yesterday’s questions and publishes any guideline changes with a version number.
Overnight Annotators label against the current guideline. Anything the guideline doesn’t cover goes to an exceptions list with the item ID, not into a guess.
Before your morning A lead reviewer samples the batch and sends a handoff note with what was done, gold-check results and the open questions.
Your morning Your team answers the questions, updates the guideline and adds the answers as new examples. The next shift starts from there.

Quality without daily calls

With few shared hours, quality checks have to be built into the queue. These are the ones that matter most.

Pilot batch first, with every question logged and the guideline revised before volume grows.
Gold checks Items with an answer your team already agreed on are mixed into the queue unflagged, so drift shows up in the data, not in your model.
Agreement checks A share of items go to two or more annotators. Frequent disagreement on a label usually means the guideline is unclear for that case.
Reviewer sampling A more senior reviewer checks a sample of each batch before it ships.
Scheduled calibration A short call at the edge of both working days, weekly or after each guideline change, keeps the written process honest.

Security and personal data

Annotators should work inside your annotation platform or a workspace you administer, never on copies of your files. Put these rules in the contract:

Named accounts with single sign-on or multi-factor authentication, and access removed the day someone leaves.
Access limited to the projects each person works on, with downloads, screenshots and copying blocked where your tools allow it.
Faces, license plates, names and other personal information blurred or removed before data reaches the team whenever the task doesn’t need them.
Managed devices and a clean workspace at the partner center, with no personal phones on the floor for sensitive projects.

Privacy rules in the delivery country

Your own privacy obligations travel with your data, and the delivery country can add its own. In the Philippines, the Data Privacy Act says a company that subcontracts the processing of personal information stays responsible for it and must make sure the processor applies proper safeguards.

In practice that means a written agreement covering what data is shared, what it may be used for, how it is protected and when it is deleted. Have your counsel confirm how your own obligations apply to the data you send.

Source: National Privacy Commission, Data Privacy Act of 2012

Wellbeing for moderation queues

Moderation is one of the most common offshore annotation tasks, and it means people look at violent, sexual or hateful material for a living. Protection has to be part of the project design.

We agree these measures with the partner center before launch: annotators know what a queue contains before they accept it, exposure per shift is limited, people rotate between sensitive and ordinary queues, images are blurred or grayscale by default where the task allows, and confidential counseling is available. Anyone can step off a sensitive queue without penalty, and the team plan has enough people that someone stepping off doesn’t stall the queue.

When nearshore is the better fit

Fewer shared hours mean slower answers to new questions. In annotation, that hurts most early in a project, when the guideline changes every few days. Keep these closer to US hours:

New tasks where the label set and edge cases aren’t settled yet.
Spanish-language or bilingual data, including chats that switch between Spanish and English. Mexico and Colombia offer native Spanish in US hours.
LLM evaluation or preference work where the rubric is still being written with your researchers.
Projects where your ML team wants to review hard cases with annotators live, several times a week.

Nearshore data annotation Mexico and Colombia for bilingual data and fast-changing guidelines.

Offshore compared with nearshore and onshore

Cost falls as distance grows, and so do shared hours. Many teams calibrate a task nearshore and then move the stable queue offshore.

	Onshore (US)	Nearshore (Mexico, Colombia)	Offshore (Philippines, India, Egypt)
Relative cost	Highest	Middle	Lowest
Shared hours with your ML team	Full	Most or all of the day	Limited unless the team works shifts
Guideline needs	Light	Moderate	Fully written, versioned and kept current
Language profile	Native English	Native Spanish, bilingual English	English; Arabic from Egypt
Best for	Expert or cleared reviewers	Bilingual data and early calibration	Volume, stable queues and overnight turnaround

Onshore vs nearshore vs offshore The three delivery models compared across all outsourced work. Data annotation outsourcing Scope, process and quality checks for an outsourced annotation team.

Frequently asked questions

What is offshore data annotation?

It’s labeling training data with a team in a distant country, such as the Philippines, India or Egypt, usually at the lowest cost of the three delivery models. The team works inside your platform on written guidelines, often overnight, and hands each batch back with review results and open questions.

Is offshore data annotation safe?

It can be, if the setup is right. Keep the data inside a platform you control, give each annotator a named account with limited access, block downloads where your tools allow it and remove personal information the task doesn’t need. Put the rules in a written agreement, and check the privacy law in the delivery country with your counsel.

How do you check quality when the team works while we sleep?

By building checks into the queue. Gold items with known answers are mixed in unflagged, some items are labeled by more than one person to see how often they agree, and a reviewer samples every batch before it ships. You get the raw results in the morning handoff note.

Which annotation tasks should not go offshore?

New tasks with unsettled guidelines, Spanish or code-switched data, and open-ended evaluation where the rubric is still changing. Those need fast back-and-forth with your team, which a nearshore team in Mexico or Colombia handles better.

How are moderation annotators protected?

Through limits agreed before launch: clear warning about what a queue contains, capped exposure per shift, rotation to ordinary queues, blurred or grayscale images by default where possible, confidential counseling and the right to step off a sensitive queue without penalty.

How much does offshore data annotation cost?

Offshore is usually the lowest-cost of the three models, followed by nearshore, then onshore. The price depends on task type, volume, guideline maturity and review depth, so we quote per scope. Don’t compare on rate alone: labels that need redoing cost more than they saved.

Find the right home for your annotation work

Tell us your data types, volume, platform and how settled your guidelines are. We’ll come back with a written plan: what can run offshore, what should stay closer and how the pilot will be checked.

Get a delivery plan