Managed annotation
An accountable team, a shared labeling guide, and a review process matched to your project.
Managed annotation. Custom workflows.
Training data,
shaped around
your workflow.
The right people. The right tools. A clearer path from raw data to reviewed, usable datasets.
✓ AI-assisted. Human-reviewed. Built around you.
REAL SATELLITE / REFERENCE LABELSSPACENET 2
LAS VEGAS · WORLDVIEW-3
Individual building footprintsInspect the sample ↗
5 FEATURED / 27 SOURCE FOOTPRINTSSpaceNet Partners · CC BY-SA 4.0 ↗
YOUR TOOLS. OUR TEAM.
Work where your data already lives.
CVATLabel StudioRoboflowLabelboxSuperAnnotateV7 Darwin
Platform-compatible workflows, shaped to your requirements. Need something different? We build that, too.
01 / WHAT WE DO
A labeling team.
A workflow that fits.
Bring us a dataset, a labeling challenge, or a process that needs to work better. We connect the people and systems to move it forward.
Image & geospatial
Objects, polygons, masks, and classifications for visual datasets, from product images to aerial and satellite imagery.
Dataset quality review
Check consistency, resolve ambiguous cases, and validate labels against your reference set and output schema.
Custom frameworks & workflows
Purpose-built annotation interfaces, integrations, and pipelines that connect your data, models, and people.
02 / INSPECT THE DELIVERABLE
The detail is
the difference.
Real images. Individual objects. Labels you can inspect and take with you. Explore the sample data, then try a review before export.
PUBLIC DATASET SAMPLE
Selected instanceSelect an outline to inspect it
Public images and benchmark labels. The review tab introduces two deliberate errors for you to resolve. This is a workflow example, not a client case study. Inspection notes are ours; source credits are above.
03 / BUILT AROUND YOUR OPERATION
Your workflow.
Without the workarounds.
When standard tools need something more, we build the missing pieces.
A custom labeling interface. A model-assisted first pass. A review queue connected to your systems. Start with a scoped prototype, then define the production handoff together.
Scope a custom workflow ↗01
→Connect
Data ingestion
Storage & APIs
02
→Assist
Model suggestions
Custom interfaces
03
→Review
Human correction
QA & exceptions
04
Deliver
Schema validation
Exports & integrations
04 / HOW WE WORK
Clear labels.
Accountable teams.
AI can speed up a first pass. People make the judgment calls. A defined process keeps the whole team aligned.
Define the task
Agree the classes, instructions, tools, output format, and acceptance criteria.
Calibrate together
A representative paid pilot aligns labels, review decisions, timing, and scope.
Annotate & review
Trained people and appropriate automation, followed by a separate quality review.
Deliver & improve
Receive the reviewed dataset, agreed exports, and findings that inform the next batch.
↳Include your requirements ↗
Data handling is part of the brief.
We agree access, approved tools, model usage, storage, retention, and deletion requirements before work begins.
05 / LET’S SHAPE THE WORK
What are
you working on?
Start with your data and the outcome you need. We’ll shape the people, tools, and review around it.
↳
A useful brief starts with the task, a representative sample, and the output you need.