Powering AI with high-quality annotated data
Accurate, consistent, QA'd annotation at the volume your pipeline needs — from bounding boxes and segmentation to video, OCR and LLM data — with quality measured, not merely promised.
The labelled data your models learn from
Computer-vision and machine-learning models are only as good as the data behind them. Inconsistent labels at scale quietly cap model accuracy — and you can't fix what you can't measure.
Cubicent delivers annotation across images, video, documents and text, built on written guidelines, a gold-standard set and multi-pass QA. We measure inter-annotator agreement and report it, so quality is visible from day one.
Model-assisted pre-labelling and human-in-the-loop workflows give you throughput without sacrificing the accuracy your models depend on.
What this service covers
- Bounding boxes & 3D cuboids
- Polygon & semantic segmentation
- Keypoints, landmarks & pose
- Video tracking & frame annotation
- OCR, NER & document AI
- RLHF & LLM data with QA
Why this work is harder than it looks.
Why annotation quality is hard to sustain at scale.
Inconsistent labelling
Without calibration, different annotators label the same object differently — and accuracy degrades as volume grows.
Quality you can't see
Annotation that isn't measured can look fine while quietly capping your model's performance.
Throughput vs accuracy
Hitting volume targets without dropping quality requires process, not just more people.
Data security
Training data is often sensitive or proprietary and can't simply be sent to an open crowd.
From pressure to predictable output.
Three pillars that make quality measurable and repeatable.
Calibrated guidelines
We turn your ontology and edge cases into a written guideline and a gold-standard set before any volume work begins.
Multi-pass QA & consensus
Sampled overlap, senior review and statistical checks against the gold standard, with inter-annotator agreement reported.
Throughput with HITL
Model-assisted pre-labelling and active learning speed work while humans verify every output.
Everything this practice delivers.
A complete annotation and AI-data catalogue.
Detection
- Bounding boxes
- 3D cuboids
- Object detection
- Attributes
Segmentation
- Semantic
- Instance
- Panoptic
- Polygon masks
Lines & Landmarks
- Polylines & lanes
- Keypoints
- Facial landmarks
- Pose estimation
3D & LiDAR
- Point clouds
- 3D cuboids
- Sensor fusion
- Tracking
Video
- Frame annotation
- Object tracking
- Interpolation
- Event tagging
OCR & Documents
- Text & regions
- Tables & fields
- Forms & invoices
- Handwriting
NLP & LLM Data
- NER
- Sentiment
- RLHF
- Prompt evaluation
QA & Evaluation
- Consensus review
- Gold standard
- Model evaluation
- Content moderation
Depth across the sectors we support.
We adapt to the conventions, compliance needs and vocabulary of each industry we work with.
Concrete artefacts, not just activity.
Every engagement produces tangible deliverables you can hold, review and build on — here is what lands in your hands.
Labelled dataset
Versioned annotations exported to COCO, YOLO, KITTI, JSON/CSV or your own custom schema.
Guidelines document
The written ontology, edge cases and decisions your data was labelled against.
QA report
Sampling results and inter-annotator agreement, so quality is a number you can see.
Format export
Delivery in your pipeline’s exact format, ready to train on with no reshaping.
A proven path from kickoff to steady state.
A quality-first workflow that compounds accuracy over the project.
Guidelines
Ontology, edge cases and rules written down.
Pilot & gold
A gold-standard set calibrates everyone.
Annotation
Production labelling with model assistance.
QA & consensus
Sampling, review and agreement metrics.
Delivery
Versioned data exported to your schema.
Feedback
Corrections improve guidelines and quality.
We work across the tools your team already uses.
Formats and platforms we work across — or your own annotation environment.
Your data is handled with care, by default.
Confidentiality is the posture, not an add-on. Engagement-specific controls are agreed up front.
NDA & least privilege
Annotators work under NDA with role-based, need-to-know access to only the data their task requires.
In-perimeter working
Where data can't leave your environment, we annotate via your VDI or secure platform, with no local copies.
Audit & traceability
Versioned images and labels with audit trails, so every annotation is accountable and reproducible.
Engage us the way the work arrives.
Start with one model and move between them as your needs change. See the Support Models page for detail.
A defined deliverable, scoped and fixed-priced up front — the simplest way to start.
Full-time resources ring-fenced for you, working inside your process and tools.
A monthly block of hours drawn down as work arrives — ideal for variable demand.
Priced per table, slide, image or ticket — the most efficient model at high volume.
An honest comparison with going it alone.
How a Cubicent engagement compares with open crowdsourcing.
| Consideration | open crowdsourcing | With Cubicent |
|---|---|---|
| Consistency | Variable | Guideline-driven |
| Measured QA | Rare | IAA reported |
| Security | Open pool | NDA & in-perimeter |
| Domain expertise | Generic | Trained teams |
| Throughput | Spiky | Planned & HITL |
Questions teams ask before they start.
Which annotation types and formats do you support?
How do you measure annotation quality?
Can you work without our data leaving our environment?
Do you support LLM data, RLHF and moderation?
Can you scale up for a large batch and back down after?
Often combined with this one.
Because everything sits under one company and one NDA, you can pull in another practice without onboarding a new vendor.
IT Infrastructure & Application Support
24×7 monitoring, an ITIL service desk and tiered L1–L3 application support that keep systems available and applications healthy.
Explore →Data Tabulation & Charting
Survey data cleaned, weighted and turned into cross-tabulation tables, banners and publication-ready charts — to your template.
Explore →Corporate Documentation Support
Production-grade PowerPoint, Word and Excel: decks, reports, templates and models, on brand and built to last.
Explore →You can’t improve what you don’t measure. We report inter-annotator agreement from day one, so quality is a number, not a promise.
Need labelled data your models can trust?
Share a sample set and your ontology; we'll run a calibrated pilot and report measured quality before scaling.