Google Cloud Software / SaaS Netherlands

ALPHAWAVE

IT Operations Automation · Marketing Personalization

ALPHAWAVE needed to scale high-quality generative video and AI automation services with a small team, which required early access to frontier models and a platform that could support both media production and internal task automation.

Reported impact

Business outcome

ALPHAWAVE scaled premium video production and AI automation services with a lean team while improving localization speed and reducing the cost of creative production for clients.

  • Cost Reduction
  • Revenue Growth
  • Speed to Market

Solution

ALPHAWAVE uses Google Cloud to address this challenge: ALPHAWAVE needed to scale high-quality generative video and AI automation services with a small team, which required early access to frontier models and a platform that could support both media production and internal task automation. Vertex AI provides the infrastructure foundation for ALPHAWAVE’s proprietary AI agents and generative AI delivery workflows, serving as the compute layer. Veo generates photorealistic product and campaign video content at much lower cost and time than CGI-heavy workflows, serving as the compute layer. Flow supports rapid production of AI-native video content alongside Veo, serving as the serving layer. Campaign concepts and client requirements move into Vertex AI-based workflows, Veo and Flow generate the video outputs, and ALPHAWAVE’s proprietary agents automate supporting browser-based tasks such as reporting and format scaling.

Data flow

Campaign concepts and client requirements move into Vertex AI-based workflows, Veo and Flow generate the video outputs, and ALPHAWAVE’s proprietary agents automate supporting browser-based tasks such as reporting and format scaling.

Solution architecture

3 components · 2 layers
  1. Compute
    • Vertex AI provides the infrastructure foundation for ALPHAWAVE’s proprietary AI agents and generative AI delivery workflows
    • Veo generates photorealistic product and campaign video content at much lower cost and time than CGI-heavy workflows
  2. Serving
    • Flow supports rapid production of AI-native video content alongside Veo

Architecture clues

  • AI agents automate browser-based reporting and format scaling tasks
  • The Philips Home Appliances work replaced expensive CGI-heavy video production
  • The company was among the first 20 EMEA firms to use Veo betas

Evidence from the source

On Veo3 and Flow, we can create a 90-second video that looks like it was filmed by a professional crew.
These agents automate repetitive browser-based tasks like reporting and format scaling.
Using Google Cloud infrastructure, like Veo and Vertex AI, ALPHAWAVE leverages early beta access and deep product partnerships to maintain a competitive advantage.
Transparency Evidence & methodology 70/100 reference value · 72% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value70/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence72%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Google Cloud

    ALPHAWAVE customer story

    First-party
    https://cloud.google.com/customers/alphawave
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Feb 7, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jan 27, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.