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Custom computer vision

The goal is not more footage. It is spotting sooner what you currently review too late.

We build computer-vision solutions for businesses that turn camera footage into reviewable detections, counts and alerts, tested on real images with human oversight.

Two real applications. One continuous path from footage to operation.

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01 / Prepare · review · test

Adaris Vision Studio

Turn representative footage into reviewed examples, teach the system what matters, test difficult scenes and prepare a ready-to-use Player.

  • Human-reviewed examples
  • Tests before deployment
  • Continuous improvement

Real captures from the applications in development

What we solve

We start with the real environment: camera positions, lighting, distance, the objects or events to recognise and the errors the process can tolerate. A standard solution may provide a base, but it is always tested and adapted with material representative of your case.

We define what the system should detect, count or follow, how we will check that it responds well and when a person must review the result. The aim is not to promise perfect recognition, but to build a solution you can evaluate and operate.

Common problems

  • A camera records, but reviewing hours of footage takes too much time
  • A standard solution fails with the angle, lighting or objects in the environment
  • Specific visual events need to be counted, classified or located
  • A prototype works on a sample but has not been validated in operation

An illustrative example

Before: a business manually reviews recordings to locate specific events and cannot consistently measure what was detected or missed.

After: an adapted system marks the defined events and retains the reference footage so a person can review uncertain cases before acting.

Illustrative computer-vision implementation cases by sector

These examples help assess where computer vision might fit; they do not describe customers, completed projects or results already obtained.

  • Retail stores: heatmaps, movement paths and queue analysis

    Video analysis can help study movement areas, dwell time and queues to inform layout decisions, using representative material and agreed criteria.

  • Construction and industry: helmets, high-visibility vests and other PPE by zone

    Visual detection can flag missing defined protective equipment inside a zone and prepare an alert for the appropriate procedure.

  • Laboratories and controlled rooms: verify measurements before requesting an opening

    A solution can check configured visual measurements before requesting an opening through an external integration; it does not replace the room's controls or authorisations.

  • Logistics: people, forklifts, goods, restricted zones and crossings

    The system can be scoped to detect people, forklifts or goods, as well as entries into restricted areas and crossings that require review or an alert.

  • Quality control: missing parts, incorrect assembly and visible defects

    It can check the presence, position or visible appearance of defined elements, validated against real examples with uncertain cases reviewed.

  • Food and pharma: gloves, masks and hairnets at critical points

    It can help check the agreed items visually at specific points, without presenting detection as a health or regulatory guarantee.

  • Parking and access: occupancy and vehicles in prohibited areas

    It can analyse occupancy, vehicles in restricted areas and access conditions to raise notices according to the site's rules.

  • Sorting and recycling: materials or objects for separation and control

    It can distinguish defined visual categories to support separation or flag incidents, provided the material and site conditions are representative.

Is your sector not listed? We can assess other processes that can be observed in images or video and have an outcome a person can check.

Assess my computer-vision case

What the engagement includes

  • Definition of classes, events and acceptance criteria
  • Preparation and review of the agreed visual material
  • Configuration and learning of the detection system
  • Testing with reserved cases to check the result
  • Pilot integration and documentation of limitations

What we need from you

  • Representative video or images obtained on a legitimate basis
  • Clear examples of correct, incorrect and ambiguous cases
  • Controlled technical access to the video stream or recordings
  • One person who validates the pilot's criteria and results

Scope and costs

Scope depends on the number of cameras, classes, environmental conditions, data volume and integration method. Data, labelling, infrastructure and third-party service usage are estimated separately and agreed in writing.

We do not promise total accuracy or biometric identification. Before processing images of people, we assess purpose, minimisation, access, retention and applicable obligations; the technical solution does not replace legal advice.

Frequent questions

Do I need to replace my cameras?

Not always. We first check resolution, angle, stability, stream format and lighting to determine whether the current equipment provides enough information.

Does the system need to be built from scratch?

Not always. We can start from a proven base and adapt it to the environment. The decision depends on the available images, the required level of accuracy and the cost of keeping it in operation.

Can it recognise specific people?

This service is framed around detecting objects, categories or events, not promising biometric identification. Any processing involving people requires a specific assessment before the solution is designed.

How will we know whether it works?

We agree in advance what it must get right, test it with examples it has not seen and review both incorrect alerts and cases it may have missed.

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Systems integration

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What the project delivers

  • Detection adapted to the environment
  • Testing on real footage
  • Alerts and human review
Adaris Vision Player: detection, movement following and analytics on real footage.