Dataset creation · Object detection · Instance segmentation

Computer vision

Automate image and video analysis with computer vision designed for the objects, events, and decisions that matter to you.

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Reviewed polygon segmentation labels on a traffic scene

Solution previewCompan-IA R&D output

All traffic imagery and video on this page derives from “Street traffic.webm” by Editor. The source was trimmed, resized, re-encoded without audio, and annotated; no endorsement is implied. Original source · CC BY 3.0 licence

The opportunity

Start with the work that needs to change.

Computer vision can locate an object, assign a label, draw a precise boundary, and turn visual information into a workflow trigger. We tailor the model and review experience to the environment in which it must perform—not just to a demo dataset.

Dataset creationObject detectionInstance segmentation

What this can include

One category. Several useful starting points.

Every engagement is tailored. These examples show the range of systems and workflows that can sit inside this service category.

Compan-IA object detection toolkit workspace

Data and annotation workspace

Transform existing video into frames, crop or resize source material, and manage labeling, datasets, training, and review from one configurable workspace.

Bounding-box annotation and review

Create and review rectangular labels, inspect visual overlays, and explicitly approve annotations before they become ground truth.

Polygon annotation and segmentation review

Trace precise object boundaries with AI- and SAM-assisted proposals, then generate annotated images and videos for visual review.

Model training workspace for a versioned segmentation dataset

Reproducible model iterations

Export numbered train, validation, and test versions in standard YOLO-style formats, orchestrate training, and connect reviewed results to the wider workflow.

Designed to be useful

What the engagement should leave behind

Faster review cycles

Use assisted annotation and visual overlays to help reviewers focus on uncertain or incorrect labels.

Reproducible datasets

Keep numbered train, validation, and test exports so model iterations can be compared and repeated.

Tailored models

Train around your own objects, camera conditions, environment, and tolerance for false detections.

Integration-ready outputs

Once validated, model outputs can be integrated into measurements, alerts, records, or wider operational workflows.

Potential applications

Useful across teams and operating contexts

01Quality inspection

02Manufacturing

03Logistics

04Asset monitoring

05Agriculture

06Video analytics

How we get there

A focused path from question to working system.

The exact scope changes by project, but the decision gates stay clear so you can learn before scaling the investment.

01Frame the workflow
02Validate the inputs
03Build and test
04Integrate and improve

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