Satvitech
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AI-powered satellite data analysis

Turning Satellite Data Into Intelligence.

Satvitech transforms suitable satellite and aerial imagery into useful insights through AI-powered object detection, change analysis, and custom geospatial solutions.

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From imagery processing to structured analytical outputs.

Real aerial photograph of a university campus with tennis courts and vehicles on the surrounding streets outlined by an object-detection model. Real image · model output
Detections by classDemo
  • Tennis courts8
  • Vehicles8

Produced by an open-source aerial detection model on public-domain USDA NAIP imagery (0.6 m, shown enlarged), confidence ≥ 0.3. Not a customer project; some objects are missed.

What we do

Four ways to turn imagery into usable information

Each service starts from a clear objective and suitable data. They can be used on their own or combined into one workflow.

Aerial-style illustration of an industrial site with outlined storage tanks and vehicles.

Object Detection & Classification

Identify and classify supported objects in suitable imagery, with annotated images and structured results.

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Aerial-style illustration of a site with newly built areas highlighted as changes.

Change Detection & Monitoring

Compare imagery captured at different times to flag visible changes and support repeat site reviews.

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Aerial-style illustration of fields with land-cover classes shaded and labelled.

Satellite Image Analytics

Extract features, surface classes and measurements from image data as structured information.

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  1. Imagery
  2. Model
  3. Output

Custom AI Solutions

Design tailored models, processing pipelines and tools for specific analysis requirements.

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Why image data needs analysis

Imagery holds the answer. Finding it is the hard part.

Satellite and aerial images can show what is on a site, how land is being used and what has changed. But turning a stack of images into a reliable answer usually means hours of manual inspection, and results can vary between reviewers and between dates.

Well-chosen AI and image-processing workflows can organise that work: they locate and count supported features, compare dates consistently and turn pixels into tables, layers and reports. They do not replace validation or expert judgement — they make it faster to apply and easier to repeat.

Manual review only

  • Time-consuming for large areas or many dates
  • Hard to keep consistent between reviewers
  • Findings often stay in notes and screenshots
  • Difficult to repeat on the next image

With an analysis workflow

  • Repeatable processing for compatible imagery
  • Consistent class definitions and review steps
  • Structured outputs: tables, layers, reports
  • Human review focused where it matters

How it works

From question to usable result in five steps

Every project follows the same disciplined path, scaled to the size of the task.

  1. Step 1: Define the objective

    Clarify what you need to identify, measure, compare or monitor — and how the answer will be used.

  2. Step 2: Select suitable imagery

    Assess sources, resolution, coverage, dates, licence conditions and image suitability for the task.

  3. Step 3: Process and analyse

    Apply the relevant image-processing, computer-vision and geospatial methods.

  4. Step 4: Validate the output

    Review results, errors, uncertainty and constraints appropriate to the task.

  5. Step 5: Deliver useful results

    Provide the agreed reports, annotated imagery, data files or a tailored workflow.

Applications

Where these methods can help

Potential application areas when suitable imagery exists for the location, dates and level of detail required.

Infrastructure

Review visible features and changes around roads, utilities, construction sites and other assets.

Industrial sites

Count and classify supported site features such as tanks, stockpiles, vehicles or rooftop installations.

Agriculture & land management

Classify field and land-cover types and compare conditions between suitable image dates.

Environmental analysis

Assess vegetation cover, cleared areas and other visible surface changes over time.

Ports & maritime facilities

Analyse port-side infrastructure and visible activity where resolution and acquisition dates allow.

Resilience & risk

Support pre- and post-event comparisons of defined areas when appropriate imagery is available.

These are areas where the methods may be useful — not a list of past projects. Feasibility is confirmed for each project once the objective and available data are clear.

Technical credibility

Good results depend on more than a model

The quality of any imagery analysis depends on the image characteristics, the source data, how well a method suits the task, and how carefully the output is validated.

Satvitech plans for all four from the start — and documents assumptions and limitations alongside every result.

Explore Our Technology
  1. Source imageryResolution, date, sensor, licence
  2. PreparationQuality checks, alignment
  3. AI analysisMethod suited to the task
  4. ValidationErrors, uncertainty, limits
  5. DeliveryAgreed files and reports

Have an imagery-analysis challenge?

Tell us what you need to identify, compare, or monitor. We’ll review the objective and the data requirements and discuss a suitable approach.

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