Google Cloud Public Sector Spain

Ayuntamiento de Valladolid

Customer Service Automation · Real-time Analytics · Security and Compliance

The city of Valladolid in Spain faces a challenge common to many medium-sized cities: managing and delivering a vast, complex web of services—from social services and public works to registrations and rural activities—across a diverse population. For citizens, finding specific information often meant navigating a tangle of departments and "invisible barriers".

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Achieved 100% factual information delivery by grounding the AI assistant in audited municipal data sources

Expanding 24/7 support to improve resident experiences

Manages 300 to 500 citizen queries daily, significantly reducing burden on traditional service channels

Provides 24/7 automated support for all municipal inquiries with gen AI agent

Reported impact

Business outcome

Provides 24/7 automated support for all municipal inquiries with gen AI agent; Manages 300 to 500 citizen queries daily, significantly reducing burden on traditional service channels; Achieved 100% factual information delivery by grounding the AI assistant in audited municipal data sources; Optimizes public spending and maximizes government responsiveness using dashboards with real-time data tracking.

Solution

Successfully transitioned from on-premises systems to a secure, flexible cloud environment using Gemini and BigQuery The centerpiece of the city’s transformation is Ana, a generative AI assistant built on Google Cloud using Gemini and with help from LuceIT. To encourage internal adoption, the council "humanized" the technology. They named the assistant after a long-serving colleague, Ana, even creating an avatar in her likeness. This helped reframe AI as an ally that handles routine administrative burdens, allowing human workers to focus on high-value citizen care. LuceIT led the technical deployment, integrating Gemini with municipal data while adhering to strict security and regulatory requirements. By using flexible infrastructure in Google Cloud, the council successfully transitioned from traditional on-prem systems to a modern cloud.

Data flow

stored or unified in BigQuery, processed with Vertex AI, and surfaced through Gemini

Solution architecture

3 components · 3 layers

Compute
- Vertex AI Hosts and orchestrates machine learning and generative AI capabilities inside the solution.
Storage
- BigQuery Stores and queries the analytics and AI-ready datasets that power the workload.
Serving
- Gemini Powers natural-language reasoning, summarization, generation, or assistance inside the workflow.

Architecture clues

Implementing secure, human-focused AI with Gemini
Products: Vertex AI
Successfully transitioned from on-premises systems to a secure, flexible cloud environment using Gemini and BigQuery

Evidence from the source

Achieved 100% factual information delivery by grounding the AI assistant in audited municipal data sources

Manages 300 to 500 citizen queries daily, significantly reducing burden on traditional service channels

Optimizes public spending and maximizes government responsiveness using dashboards with real-time data tracking

Provides 24/7 automated support for all municipal inquiries with gen AI agent

Successfully transitioned from on-premises systems to a secure, flexible cloud environment using Gemini and BigQuery

Transparency Evidence & methodology 100/100 reference value · 79% confidence · 1 source

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

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 value100/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth25/25
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 impact25/25
4 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence79%

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
5 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 specificity10/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

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

Google Cloud
Ayuntamiento de Valladolid customer story

First-party
https://cloud.google.com/customers/valladolid

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 Mar 21, 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 Mar 19, 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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