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ZINDORA

Flagship solution

ZINSEAS

AI-Powered Earth Observation Intelligence for Kenya's Maritime Environments

In development Actively being built and tested.

ZINSEAS combines Earth Observation, vessel-tracking data, environmental intelligence and explainable AI to create a clearer, evidence-based picture of activity across Kenya's maritime environment.

ZINSEAS INTELLIGENCE Prototype · illustrative

Layers

  • EO detections
  • AIS tracks
  • Marine protected areas
  • Satellite footprint
  • Environmental layer
  • Bathymetry

Source

Copernicus Sentinel-1
AIS · environmental
Positions synthetic

Kiunga Malindi Watamu Mombasa Kisite-Mpunguti ANOMALOUS no AIS correlation S1 IW SWATH · INDICATIVE ~111 km

Alert

Anomalous activity detected

Confidence 92%

Evidence

  • EO detection

    Sentinel-1 IW, descending pass

  • AIS discrepancy

    No corresponding position report

  • Historical activity pattern

    Outside observed pattern for cell

  • Geographic context

    Within nearshore management area

Requires human verification

ZINSEAS does not determine legality. It prioritises observations for review by the responsible authority.

Illustrative interface. Vessel positions, tracks and confidence values shown here are synthetic and are used to communicate the concept. Coastline and marine protected areas are real. No operational results are represented.

Four sources. One picture.

No single feed describes what is happening at sea. Each one answers a different question, and the useful answer lives in the disagreement between them.

  1. 01 Satellites observe what is happening.
  2. 02 Vessel data provides reported activity.
  3. 03 Environmental data provides context.
  4. 04 AI brings these observations together.
  5. 05 ZINSEAS transforms them into actionable intelligence.

Making the maritime environment more observable.

Maritime environments are vast, dynamic and difficult to monitor continuously. A patrol vessel sees a few square kilometres at a time. A reporting system sees only the vessels that choose to report. Weather closes the window on optical observation for weeks at a stretch.

The result is not an absence of data but an absence of a joined-up picture, and decisions get made on whichever fragment happened to be available.

ZINSEAS is designed to help decision-makers

  • Detect anomalous maritime activity
  • Combine fragmented information sources
  • Prioritise areas requiring human attention
  • Monitor environmental change
  • Support fisheries and maritime management
  • Improve evidence-based decision-making

AI

prioritises

EO

provides scale

Humans

make decisions

ZINSEAS does not replace human authorities, and is not designed to.

From observation to intelligence.

A pipeline, not a diagram. Each stage takes a larger volume of input and returns a smaller volume of something more decisive.

  1. Observe

    01
    • Sentinel-1
    • Sentinel-2
    • Other EO
    • AIS / VMS
    • Environmental data

  2. Fuse

    02
    • Data engineering
    • Geospatial processing
    • Multimodal AI
    • Temporal analysis

  3. Understand

    03
    • Vessel intelligence
    • Anomaly detection
    • Environmental intelligence
    • Risk indicators
    • Change detection

  4. Act

    04
    • Evidence
    • Alerts
    • Decision support
    • Analytics
    • APIs

The observations underneath.

We exploit Copernicus Sentinel data to build downstream intelligence applications. The missions are operated by ESA and the European Commission; what we build is the analysis layer on top of the data they make openly available.

Sentinel-1

C-band SAR

SAR-based observation for all-weather, day/night monitoring.

Radar is unaffected by cloud and does not need daylight, which matters on a coast with a long monsoon season. Metal hulls return strongly against a rougher sea surface, which is what makes vessel detection possible at all.

  • Active radar
  • Cloud-independent
  • Day and night

Sentinel-2

Multispectral optical

Multispectral Earth Observation for land, coastal and environmental applications.

Thirteen spectral bands at 10, 20 and 60 metre resolution support water quality, coastal habitat and land-cover analysis, and give radar detections a visual corroboration when the sky is clear.

  • 13 spectral bands
  • 10-60 m resolution
  • Optical, needs daylight

Complementary sources

Open and commercial

Additional EO integrated where the application justifies it.

Higher-resolution commercial imagery, thermal and altimetry data can be brought in where a specific question needs them. The architecture treats sources as interchangeable inputs rather than building around any single one.

  • Source-agnostic design
  • Open data first

Intelligence you can interrogate.

ZINSEAS is designed around explainability, confidence and human verification. An output nobody can trace back to an observation is not evidence, and presenting it as though it were is how automated systems lose the trust of the people who have to act on them.

No black-box enforcement decisions.

Evidence
The observations the inference was drawn from
Confidence
A stated level, not a binary verdict
Sources
Which sensor, which pass, which feed
Context
Environmental and historical conditions at the time
Timestamp
Acquisition and processing times, separately
Processing
Model version and processing chain

From data to decisions.

  1. Raw data
  2. Processed observations
  3. AI models
  4. Intelligence
  5. Decision support
  6. Measurable impact

Designed for

The organisations whose decisions this kind of intelligence is meant to support. Zindora has no commercial deployments and names no customers.

  • Public authorities
  • Fisheries and maritime organisations
  • Conservation organisations
  • Marine spatial planning stakeholders
  • Blue-economy businesses
  • Research institutions
  • Environmental organisations

From feasibility to deployment.

ZINSEAS is being developed as an Earth Observation innovation focused on technical feasibility, validation and MVP development in Kenya.

Programme context

ZINSEAS is being developed in alignment with the objectives of the ABIL EXPLORE programme.

  • Africa-EU Space Partnership Programme
  • Africa Business Innovation Lab (ABIL) - EXPLORE

Zindora does not claim selection, funding or endorsement by ESA, the Kenya Space Agency or ABIL. This page states an alignment of objectives only.

Working on Kenya's maritime environment?

We are looking for the institutions, researchers and operators whose questions should be shaping what ZINSEAS becomes.

Talk to us about ZINSEAS →