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GETA AS

Organization number 995318733 · Aksjeselskap

Programmatic access to company data (JSON)

Source: Firmafakta. Data read and page generated 2026-09-09T14:24:00Z. 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:
995318733
navn:
GETA AS
organisasjonsform:
kode:
AS
beskrivelse:
Aksjeselskap
naeringskode1:
kode:
62.100
beskrivelse:
Dataprogrammeringstjenester
antallAnsatte:
15
hjemmeside:
geta.no
epostadresse:
andre@geta.no
telefon:
not reported by source
forretningsadresse:
adresse:
Skippergata 4
poststed:
OSLO
postnummer:
0151
kommune:
OSLO
stiftelsesdato:
2010-03-03
registreringsdatoenhetsregisteret:
2010-04-12
aktivitet:
Fremstilling/salg av IT-relaterte produkter og tjenester, samt andre, produkter som naturlig faller sammen med dette, herunder å delta i, andre selskaper med lignende virksomhet, kjøp og salg av aksjer, eller, på annen måte gjøre seg interessert i andre foretagender.
vedtektsfestetFormaal:
Fremstilling/salg av IT-relaterte produkter og tjenester, samt andre, produkter som naturlig faller sammen med dette, herunder å delta i, andre selskaper med lignende virksomhet, kjøp og salg av aksjer, eller, på annen måte gjøre seg interessert i andre foretagender.

View the address in Geonorge

Board and other roles

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

Daglig leder

Revisor

Styre

Owners

Source: Firmafakta shareholder dataset.

  1. BINARY AS – 26.0 % (78000 shares, share class: Ordinære aksjer)
  2. VIG HOLDING AS – 26.0 % (78000 shares, share class: Ordinære aksjer)
  3. FINI AS – 24.0 % (72000 shares, share class: Ordinære aksjer)
  4. MANGSET AS – 12.0 % (36000 shares, share class: Ordinære aksjer)
  5. STENIT – 12.0 % (36000 shares, share class: Ordinære aksjer)

Fetch a longer owner list

Company holdings

Grants and support

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

Innovasjon Norge (0)

No registered grants.

EU-tildelinger (0)

No registered grants.

Forskningsrådet (0)

No registered grants.

SkatteFUNN (3)

3 results

  1. id:
    35347
    innsendt_dato:
    2015-02-19
    prosjektnummer:
    248297
    bedriftsnavn:
    GETA AS
    prosjekttittel:
    Multimedial mediehub
    organisasjonsnummer:
    995318733
    fylke:
    Oslo
    kommunenavn:
    Oslo
    poststed:
    OSLO
    soknad_godkjent:
    JA
    soknad_avslatt:
    NEI
    vedtaksdato:
    2015-02-26
    prosjekt_fra_ar:
    2015
    prosjekt_til_ar:
    2015
    sammendrag:
    not reported by source
  2. id:
    29769
    innsendt_dato:
    2012-11-30
    prosjektnummer:
    227352
    bedriftsnavn:
    GETA AS
    prosjekttittel:
    Multimedial mediehub
    organisasjonsnummer:
    995318733
    fylke:
    Oslo
    kommunenavn:
    Oslo
    poststed:
    OSLO
    soknad_godkjent:
    JA
    soknad_avslatt:
    NEI
    vedtaksdato:
    2013-02-21
    prosjekt_fra_ar:
    2013
    prosjekt_til_ar:
    2014
    sammendrag:
    not reported by source
  3. id:
    60079
    innsendt_dato:
    2020-08-31
    prosjektnummer:
    319408
    bedriftsnavn:
    GETA AS
    prosjekttittel:
    Story X
    organisasjonsnummer:
    995318733
    fylke:
    Oslo
    kommunenavn:
    Oslo
    poststed:
    OSLO
    soknad_godkjent:
    JA
    soknad_avslatt:
    NEI
    vedtaksdato:
    2020-11-18
    prosjekt_fra_ar:
    2020
    prosjekt_til_ar:
    2021
    sammendrag:
    Many companies struggle to write good product descriptions for their products. Product descriptions are important because they help customers understand the product and increase the conversion rate. If the product description is poorly written, it will only cause confusion and frustration for the customer. Writing good product descriptions is for many companies a nearly impossible task because when the product catalog is large and descriptions have to be available in multiple languages. It takes a lot of time and is very costly when external companies are hired. To solve this problem we will use natural language processing (machine learning) to automatically write high-quality product descriptions. Descriptions are generated based on the product specifications and writing-style of the company to follow the company's brand guidelines. In order to support a large product, catalog descriptions will be generated in batches. All descriptions are evaluated and validated by using an advanced algorithm. With this solution, companies will be able to efficiently generate a good description of each of their products.

Subunits

Open positions

count:
0
stillinger:

No results.

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How an AI agent should use this page

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How to use the company page

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