FORESTSAT AS

Organization number 929051971 · Aksjeselskap

Programmatic access to company data (JSON)

Source: Firmafakta. Data read and page generated 2026-09-10T16:25:27Z. HTML cache: no-store (TTL 0 seconds). Default TTL for Firmafakta JSON/API responses: 60 seconds.

Facts

Source: Firmafakta, with business data from public registers.

organisasjonsnummer:
929051971
navn:
FORESTSAT AS
organisasjonsform:
kode:
AS
beskrivelse:
Aksjeselskap
naeringskode1:
kode:
62.100
beskrivelse:
Dataprogrammeringstjenester
antallAnsatte:
not reported by source
hjemmeside:
not reported by source
epostadresse:
not reported by source
telefon:
not reported by source
forretningsadresse:
adresse:
Lersolveien 12
poststed:
OSLO
postnummer:
0876
kommune:
OSLO
stiftelsesdato:
2022-03-01
registreringsdatoenhetsregisteret:
2022-04-07
aktivitet:
ESG-fokusert selskap som utvikler og selger software tjenester.
vedtektsfestetFormaal:
Utvikle software for å bekjempe skogbranner.

View the address in Geonorge

Board and other roles

Source: Firmafakta. Also see the separate Brønnøysund lookup under related lookups.

Bostyrer

  • Bostyrer:

Daglig leder

Styre

Owners

Source: Firmafakta shareholder dataset.

  1. AJAY GOYAL – 74.76 % (785 shares, share class: Ordinære aksjer)
  2. JL INVESTMENT AS – 12.57 % (132 shares, share class: Ordinære aksjer)
  3. BHASKAR, CHAUGULE – 10.0 % (105 shares, share class: Ordinære aksjer)
  4. CAGE INVEST AS – 1.05 % (11 shares, share class: Ordinære aksjer)
  5. ALEXANDRE CIEZA – 0.48 % (5 shares, share class: Ordinære aksjer)
  6. FJOMP AS – 0.48 % (5 shares, share class: Ordinære aksjer)
  7. JC-INVEST AS – 0.48 % (5 shares, share class: Ordinære aksjer)
  8. YULIYA, YAZVINSKAYA – 0.19 % (2 shares, share class: Ordinære aksjer)

Fetch a longer owner list

Company holdings

No holdings found.

Grants and support

Sources provided through Firmafakta: Innovation Norway, the EU, the Research Council of Norway and SkatteFUNN.

Innovasjon Norge (1)

1 results

  1. fylkesnavn:
    Oslo
    kommunenavn:
    Oslo
    org_nr:
    929051971
    bedriftsnavn:
    FORESTSAT AS
    virkemiddelkategori:
    Oppstartstilskudd
    underkategori:
    Landsdekkende etablerertilskudd
    innvilget_belop:
    100000
    innvilget_dato:
    22.07.22
    beslutningsenhet:
    IN Kommersialisering og vekst
    naringshovedgruppe:
    K - Telekommunikasjon, dataprogrammering, konsulentvirksomhet, datainfrastruktur og andre tjenester tilknyttet informasjonsteknologi
    naring:
    62.100 Dataprogrammeringstjenester
    type_finansiering:
    Tilskudd

EU-tildelinger (0)

No registered grants.

Forskningsrådet (0)

No registered grants.

SkatteFUNN (1)

1 results

  1. id:
    65717
    innsendt_dato:
    2022-08-31
    prosjektnummer:
    339712
    bedriftsnavn:
    FORESTSAT AS
    prosjekttittel:
    Satellite Earth Observation AI for Forest Fire Prevention
    organisasjonsnummer:
    929051971
    fylke:
    Oslo
    kommunenavn:
    Oslo
    poststed:
    OSLO
    soknad_godkjent:
    JA
    soknad_avslatt:
    NEI
    vedtaksdato:
    2022-11-09
    prosjekt_fra_ar:
    2022
    prosjekt_til_ar:
    2024
    sammendrag:
    ForestSAT uses Machine Learning to process earth observation imagery and remote sensing data to analyze forest degradation over the years and predict fire risk in areas at risk with substantial fuel buildup. ForestSAT AI Decision Support System aims to provide actionable intelligence for fire risk mitigation through data driven smart forest management. The AI DSS will provide recommendations for timely action of regeneration of forest for and reforestation, improved forest resilience against wildfires, improved carbon sequestration and minimizing risk of emissions from uncontrolled wildfire destruction and deforestation. Our Machine Learning algorithms process petabytes of satellite images, multispectral remote sensing data, topographical, aerial LiDAR & ground sensory data with human inputs to examine forest floor fuel buildup, tree & vegetation status, climate and anthropogenic cause & effect. ForestSAT will make accurate future predictions of wildfire areas-at-risk polygons in millions of scanned hectares of forest to enable effective preventive actions.

Open positions

count:
0
stillinger:

No results.

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