What types of data can Label Less annotate?

Image and video, text and language with Cantonese and Traditional Chinese local context, audio and speech, and robotics and teleoperation data such as sensor, LiDAR, trajectories and action segments.

How does Label Less ensure quality?

Every annotator is trained against clear guidelines, and each batch passes multi-pass review and consensus checks before delivery, with auditable workflows you can verify.

How is our data kept secure?

Projects run under signed confidentiality agreements with access-controlled, managed workflows so your data stays protected from intake to delivery.

          Data annotation, made human · Hong Kong
        

Data, precisely labeled. People, finallyun-labeled.

Q: What is data annotation?

Data annotation, or data labeling, is the process of tagging images, text, audio, sensor and robotics data so machine-learning models can learn from them. It is the human foundation that makes AI accurate.

Q: Who does the labeling work?

Trained annotators from underserved communities in Hong Kong, including single parents, people with disabilities and those managing chronic illness, supported by social workers and a quality team.

Q: How do I start a project?

Tell us your formats, volume and timeline, and we will scope a pilot and quote with clear quality targets. Most clients start with a small paid pilot.

Label Less is a Hong Kong social enterprise and a bridge that connects organizations needing high-quality labeled data with underserved talent we train and support: single parents, people with disabilities, and those living with long-term illness.

Start a project → How it works

Impact Innovation Lab · Cohort 4 · Backed by the SIE Fund

The model

A bridge between data and social responsibility.

On one side, surging demand for labeled data. On the other, talented people shut out of work. Label Less connects them, with training and QA that make the data dependable.

Demand

Corporates, AI labs and research institutes that need accurately labeled training data.

Label Less

We recruit, train, manage and quality-check. The result is reliable, model-ready data.

Talent

We partner with NGOs serving the underprivileged: single parents, people with disabilities and patients with chronic illness, and help them build careers in tech.

Data we label local context → robotics

From local context to robot teleoperation.

VIS

Image & video

Bounding boxes, polygons, semantic segmentation, keypoints and classification for computer vision.

LANG

Language & local context

Cantonese and Traditional Chinese, Hong Kong nuance, NER, sentiment, intent and content moderation.

AUD

Audio & speech

Transcription, speaker labeling, timestamping and acoustic event tagging across dialects.

ROBO

Robotics & teleoperation

Sensor and LiDAR labeling, trajectories, action segments and teleoperation demonstrations.

Quality assurance

Multi-pass review and consensus on every batch, with secure, auditable delivery.

Quality

Trained people. Verified data.

People who make exceptional annotators

We select for care, focus and commitment. Those traits turn straight into accurate labels.

›Patient, detail-oriented and genuinely invested.
›Flexible hours that fit around care and health.
›Onboarded and supported with NGOs and social workers.

Quality you can verify

Every project runs a structured pipeline built for accuracy, consistency and confidentiality.

›Clear guidelines and hands-on training before any labels ship.
›Multi-pass review and consensus on every batch.
›NDA-backed, access-controlled handling end to end.

Train

Annotators learn your spec and edge cases.

Annotate

Careful labeling at a pace that protects quality.

Review

Multi-pass QA and consensus before sign-off.

Deliver

Model-ready data in your format, on schedule.

The people behind the labels.

We build careers with people the job market overlooks, starting in Hong Kong and expanding from there.

Showcase

Single parents

Working in the hours between childcare, earning a stable income from home.

Inclusive

People with disabilities

Remote, flexible work that meets each person where they are.

Adaptive

Living with chronic illness

Meaningful work that adapts around treatment and recovery.

Impact

Every label is recognition.

Behind better AI is better work. We turn demand for training data into stable, flexible income for people facing exclusion.

30+

people in our pilot cohort

2-3h

flexible work hours, around life

100%

remote-friendly, done from home

data specialisms, one team

Why we're called Label Less.

The name is also a promise: to put fewer labels on people. Single parent. Disabled. Patient. We help shed those labels by labeling the data that powers AI.

Label Less is a Cohort 4 project of MakerBay's Impact Innovation Lab and is backed by the SIE Fund. We pair growing demand for AI training data with people the tech economy overlooks. Each project builds their skills, income and confidence.

“AI should enable every member of society.”

What's next

› Career ladders › New communities › Across the region

Read the full story ↗

For organizations

Have data that needs labeling?

Tell us your formats, volume and timeline. We'll scope a pilot and quote with clear quality targets.

Request a quote →

For supporters

Want to back the mission?

Join the program, partner with us, or help us reach more people across Hong Kong.

Get involved →

Data annotation, answered.

What is data annotation? +

What types of data can you label? +

How do you ensure quality and accuracy? +

Who actually does the labeling? +

How do you keep our data secure? +

How do I start a project? +