High-Precision Ground Truth Data for the World's Best AI Teams.
Dedicated, managed annotation teams for autonomous vehicles, retail, agritech and generative AI — with the security of an in-house team.
- ◆Independent & Neutral
- ◆Managed in-office teams
- ◆2D · 3D · LiDAR · RLHF
- ◆Cyprus HQ → Dhaka delivery
points ~38,400
objects 0
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.
Independent ownership
No Big-Tech parent, no conflicted incumbent. A pure-play partner with no agenda but your model's accuracy.
Contractual data firewalls
Your data is handled by a dedicated team under signed NDAs, within controlled environments — never farmed out.
Your ground truth stays yours
Client-owned IP and outputs. We're an extension of your ML team, not a window into it.
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.
Image & Video Annotation
- 2D bounding boxes & polygons
- Semantic & instance segmentation
- Keypoints, landmarks & pose
- Object tracking across frames
3D LiDAR & Sensor Fusion
- 3D cuboids in point clouds
- Camera · LiDAR · radar fusion
- Lane & drivable-area segmentation
- Occlusion & truncation states
Language & Generative AI
- Text classification & NER
- Sentiment & intent labeling
- RLHF preference ranking
- Red-teaming & safety review
OCR & Structured Data
- OCR for pricing, labels & forms
- Document layout & structure
- Audio transcription
- Data validation & QA passes
Verticalized teams that already speak your domain.
Phase 1 focus — high-volume, high-precision annotation across four core verticals.
Autonomous Vehicles & Robotics
Perception-grade ground truth for the road and the factory floor.
- 2D / 3D bounding boxes
- LiDAR point-cloud annotation
- Lane segmentation
- Pedestrian tracking
Retail & E-Commerce AI
Turn shelves, products and pages into structured signal.
- Product classification
- Shelf & planogram detection
- Visual search tagging
- OCR for pricing & labels
Agriculture Tech
From drone imagery to crop health, labeled at field scale.
- Crop disease detection
- Drone imagery segmentation
- Yield estimation labeling
- Plant & weed classification
Generative AI & NLP
The nuanced human feedback advanced models depend on.
- Text classification
- Sentiment analysis
- RLHF & preference data
- Prompt & response evaluation
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.
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
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
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.
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.
Built for the hardest labels.
Our managed model is designed to scale into deep domain expertise — from autonomous-driving edge cases today toward specialist-grade work tomorrow. We're building toward expert medical annotation, drawing on Bangladesh's deep pool of medical graduates, under a compliance-first roadmap.
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.