Normalized claim
Time: 24 hours
Data scientists can now operate autonomously in 24 hours.
Facile.it case study (Gemini Enterprise Agent Platform, Vertex AI integration)
Use case typeCustomer experience analyticsUpdated Jun 13, 2026
Facile.it is one of the main Italian online price comparison platforms in the market of insurance products, utilities and financial products. The customer case study describes how Google Cloud technologies were used to centralize data management, speed up machine learning model training and deployment, and improve customer experience and conversion performance.
Reported outcomes
5x
quantified impactOther quantified impact
24 hourstime100xquantified impact+15%quantified impact+20%quantified impact
Strategic outcomes
Speed & agilityAccelerated model training and deploymentEmployee experienceEnabled autonomous data scientistsScale & capacityExpanded data analysis capacityNew product / capabilityImproved A/B testing capability
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 100 x increase
The volume of data analyzed increased 100x.
Normalized claim
Quantified impact: 5 x increase
A/B tests increased 5x.
Normalized claim
Quantified impact: 15% increase
Conversion rate improved by +15% to +20%.
Normalized claim
Quantified impact: 20% increase
Conversion rate improved by +15% to +20%.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Facile.it
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Stories
Accelerate execution and operational throughput with an agentic approach
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Customer Experience
- 2Analytics
- 3Workflow Automation
- Reduce time and effort required to execute tasks and integrate AI-driven capabilities into insurance workflows.
- Accelerate execution and operational throughput with an agentic approach.
- Improve reliability and speed of analysis across online and offline data.
- Implemented Gemini Enterprise Agent Platform capabilities and integrated with Vertex AI.
- Combined Vertex AI with BigQuery for machine learning and analytics workflows.
- Centralized data in BigQuery to support a unified user view and faster model development.
- Model training and deployment went from a whole working week to one day.
- Data scientists can now operate autonomously in 24 hours.
- The volume of data analyzed increased 100x.
- A/B tests increased 5x.
- Conversion rate improved by +15% to +20%.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jun 3, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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