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Google Cloud Software / SaaS The Netherlands

UNETI AI Labs

IT Operations Automation

She can also manage rules specific to certain sectors, such as in healthcare where actors must manage specific workflows before obtaining regulatory certifications.

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Already up to 7 hours of work automated per employee each week
Finally, UNETI AI Labs also appreciated the simplicity of deploying Google Cloud services. "AI agents are destined to become true critical applications, which must operate 24/7 with a very high level of reliability," specifies Roberto…
Founded in 2019 and based in the Netherlands, UNETI is a venture capital player specializing in emerging technologies, including FinTech, MedTech, GreenTech, and IndustryTech. Its operational technology branch, UNETI AI Labs, develops…

Reported impact

Business outcome

Already up to 7 hours of work automated per employee each week; Enhanced execution quality on critical processes with "digital colleagues"; Reduced operational load thanks to Google Cloud managed services

  • Compliance
  • Customer Experience
  • Productivity Improvement
  • Risk Reduction

Solution

She can also manage rules specific to certain sectors, such as in healthcare where actors must manage specific workflows before obtaining regulatory certifications. Using Gemini, Vertex AI, and AgentSpace, UNETI AI Labs developed two AI agents that provide advanced operational support. These agents act as digital colleagues integrated into daily workflows, executing critical tasks with a rigor comparable to that of a… To build these agents, UNETI AI Labs relies entirely on Google Cloud, particularly Gemini, Vertex AI, and AgentSpace. The primary criterion guiding this choice was security, as Roberto Ramadhin explains: "Our data is sensitive, and we needed an environment… Key components include Gemini models provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis; Vertex AI provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis; Agent Builder coordinates.

Solution architecture

7 components · 3 layers
  1. Compute
    • Gemini models Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
    • Vertex AI Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
    • Cloud Run Runs serverless or virtualized application services with elastic scale for production AI workloads.
  2. Orchestration
    • Agent Builder Coordinates multi-agent workflows, tool calling, and governed automation across the application.
    • AgentSpace Coordinates multi-agent workflows, tool calling, and governed automation across the application.
    • Cloud Scheduler Orchestrates scheduled workflows and service-to-service jobs across the platform.
  3. Uncategorized
    • (including Supports a core part of the deployed AI and data workflow described in the customer story.

Architecture clues

  • "Davis and Nance are not theoretical concepts: we use them every day internally to manage our own operations," explains Maikel Lobbezoo. "Today, they are already saving each employee nearly seven hours per week on…
  • To build these agents, UNETI AI Labs relies entirely on Google Cloud, particularly Gemini, Vertex AI, and AgentSpace. The primary criterion guiding this choice was security, as Roberto Ramadhin explains: "Our data is…
  • UNETI is structured around two complementary entities. UNETI Ventures, on one side, invests in high-potential startups and supports their leaders over the long term. UNETI AI Labs , on the other, designs tools, AI…
  • Using Gemini, Vertex AI, and AgentSpace, UNETI AI Labs developed two AI agents that provide advanced operational support. These agents act as digital colleagues integrated into daily workflows, executing critical tasks…
  • With this in mind, UNETI AI Labs has developed two AI agents that embody its vision of reinforced operational support: Davis and Nance. Far from simple conversational assistants, these agents are designed as true…

Evidence from the source

Already up to 7 hours of work automated per employee each week
Enhanced execution quality on critical processes with "digital colleagues"
Reduced operational load thanks to Google Cloud managed services
To build these agents, UNETI AI Labs relies entirely on Google Cloud, particularly Gemini, Vertex AI, and AgentSpace. The primary criterion guiding this choice was security, as Roberto Ramadhin explains: "Our data is…
Using Gemini, Vertex AI, and AgentSpace, UNETI AI Labs developed two AI agents that provide advanced operational support. These agents act as digital colleagues integrated into daily workflows, executing critical tasks…
With this in mind, UNETI AI Labs has developed two AI agents that embody its vision of reinforced operational support: Davis and Nance. Far from simple conversational assistants, these agents are designed as true…
Transparency Evidence & methodology 80/100 reference value · 77% 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 value80/100
  • 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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence77%
  • 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 evidence20/20
    6 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

    UNETI AI Labs customer story

    First-party
    https://cloud.google.com/customers/uneti-ai-labs
    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 17, 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 28, 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.

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