Independent · Neutral · In-office

High-Precision Ground Truth Data for the World's Best AI Teams.

Labelix is an independent data annotation company: dedicated, managed teams for image, document, audio and video AI, with the security of an in-house team.

  • Independent & Neutral
  • Managed in-office teams
  • Image · Document · Audio · Video
  • Cyprus HQ → Dhaka delivery
Why Labelix · Why now

The independence your training data deserves.

The annotation industry is consolidating into the hands of the AI giants. When your labeling partner is owned by a competitor, your training data — and the roadmap it quietly reveals — no longer sits on neutral ground. Labelix exists in that exact gap: independent, neutral, and accountable only to you.

01

Independent ownership

No Big-Tech parent, no conflicted incumbent. A pure-play partner with no agenda but your model's accuracy.

02

Contractual data firewalls

Your data is handled by a dedicated team under signed NDAs, within controlled environments — never farmed out.

03

Your ground truth stays yours

Client-owned IP and outputs. We're an extension of your ML team, not a window into it.

Capabilities

Every modality your model needs — labeled by people, not guesswork.

Pixel-perfect work on the complex edge cases automated tools miss — across vision, 3D, language and documents.

CV · 2D

Image & Video Annotation

  • 2D bounding boxes & polygons
  • Semantic & instance segmentation
  • Keypoints, landmarks & pose
  • Object tracking across frames
Docs · OCR

Document AI & OCR

  • OCR & transcription
  • Key-value & field extraction
  • Layout & table structure
  • Document classification & QA
Audio · Video

Audio, Speech & Video

  • Audio transcription
  • Speaker & diarization labeling
  • Event & sound tagging
  • Video object & action labeling
NLP · Text

Text & Language

  • Text classification & NER
  • Sentiment & intent labeling
  • Entity & relationship tagging
  • Content categorization & QA
The Workforce Model

An extension of your team — not a crowd of strangers.

The difference between a managed in-office workforce and a crowdsourced platform is the difference between a partner and a liability.

Managed · in-office · accountable

The Labelix model

  • Dedicated, full-time specialists
  • Secure, access-controlled facilities
  • Vetted staff under signed NDAs
  • Data stays in a controlled environment
  • Consistent teams that learn your edge cases
  • A direct extension of your ML team
Anonymous · transient · unaccountable

The crowdsourced model

  • Anonymous, rotating gig workers
  • Sensitive data on personal laptops
  • Little vetting or accountability
  • Quality that swings task to task
  • No retained domain knowledge
  • Your data scattered across the globe
Security & Trust

Built like a company you'd trust with proprietary data.

We don't farm sensitive client data to anonymous workers. Annotation happens with dedicated teams, in controlled environments, under contractual protection.

On our compliance roadmap
ISO 27001SOC 2 Type IIHIPAA (medical vertical)

Planned certifications as we scale. We'll publish each one only when independently audited and granted.

In-office, access-controlled

Work happens in monitored facilities — not on personal devices in coffee shops.

Dedicated teams under NDA

Vetted, trained, full-time personnel assigned to your project and bound by signed agreements.

Controlled data handling

Your data is accessed within a controlled environment, with contractual firewalls around it.

Client-owned IP

Every label and output belongs to you. We're a partner, never a competitor.

Where we're headed

Built for the hardest labels.

Our managed model is built to scale from today's high-volume image, document and audio work into deeper specialist annotation — sensor-fusion and 3D, and expert domains like medical — on a compliance-first roadmap, drawing on Bangladesh's deep STEM and medical-graduate talent.

The people behind Labelix

Quality is personal here.

Not a platform with a support queue. A founder on the ground in Dhaka who owns your batches.

Rashid Arif, Co-Founder · Delivery (Dhaka)

Rashid Arif

Co-Founder · Delivery (Dhaka)

For 9 years I've brought brilliant people from Bangladesh to companies around the world. The deeper I went into AI, the clearer it became: models don't replace people, they run on them.

Labelix is that team: specialists who learn your domain and your standards and make your models better. We're taking on our first partners now.

LinkedIn
Start with a pilot

Put a dedicated team on your hardest labels.

Send us a representative sample. We'll scope a pilot, label it to spec, and show you the quality difference a managed, in-office team makes.

support@labelix.ai