What challenges did Metrovacesa face before AI implementation?

Metrovacesa faced high lead volumes with manual qualification bottlenecks and limited service outside business hours, especially for international multilingual customers. Call center limitations led to missed opportunities on weekends and evenings when conversions were higher. The company sought an enterprise-grade conversational AI solution for scalable, intelligent customer engagement and data-driven insights.

What was the impact of the AI solution?

Achieved 94.8% performance improvement and 38% reduction in service time. Handled 56% of conversations outside traditional hours, capturing significant business opportunities. Automated 84.5% of engagements and qualified over 4,500 leads efficiently. User satisfaction rose to 77% with an average score of 8.75/10. Unlocked 33% of business occurring off-hours, particularly on Sundays with over 50% conversion rates.

Source

GCP

Metrovacesa Intelligent Assistant (MiA) Conversational AI for Real Estate Lead Qualification

Use case typeConversational supportUpdated Jun 13, 2026

Metrovacesa, a leading Spanish real estate developer, partnered with Lutech to deploy MiA, an intelligent assistant built on Google Cloud for multilingual 24/7 customer support and lead qualification. Using Dialogflow CX and Vertex AI, MiA manages over 100 developments with sub-five-second responses and automates 84.5% of interactions, improving efficiency and customer satisfaction. MiA integrates with Dynamics 365 CRM to enrich customer profiles and supports high scalability using Google Cloud serverless infrastructure and Lutech's expertise. The platform provides strategic data insights via Looker Studio dashboards to enhance commercial and marketing strategies. Planned future innovations include hyper-personalization with generative AI using Gemini and Vertex AI, multimodal user input, and integration with Google Maps for enriched query responses.

Organization: Metrovacesa
Industry: Real Estate
Location: Spain

Reported outcomes

−94.8%

timeTime & speed

−38%time56%time84.5%quantified impact77%quantified impact33%time

Strategic outcomes

Speed & agilityEnabled 24/7 multilingual supportNew product / capabilityDeployed AI lead qualification assistantBetter decisions & insightProvided strategic data insightsScale & capacityAutomated lead engagement at scale

Primary read

Use case focus

Showing 2 of 2

1Conversational AI for lead qualification
2Multilingual customer support automation

Metrovacesa faced high lead volumes with manual qualification bottlenecks and limited service outside business hours, especially for international multilingual customers.
Call center limitations led to missed opportunities on weekends and evenings when conversions were higher.
The company sought an enterprise-grade conversational AI solution for scalable, intelligent customer engagement and data-driven insights.

Deployment of a multi-agent conversational AI system using Google Cloud Dialogflow CX, Vertex AI, and Gemini models.
Integration with Dynamics 365 CRM and Looker Studio for customer data enrichment and performance analytics.
Implementation on Google Cloud serverless infrastructure for automatic scaling and high availability.
Collaboration with Lutech for rapid deployment and ongoing AI architecture enhancement.

Technologies

Vertex AI Dialogflow CX Gemini Looker Studio

Achieved 94.8% performance improvement and 38% reduction in service time.
Handled 56% of conversations outside traditional hours, capturing significant business opportunities.
Automated 84.5% of engagements and qualified over 4,500 leads efficiently.
User satisfaction rose to 77% with an average score of 8.75/10.
Unlocked 33% of business occurring off-hours, particularly on Sundays with over 50% conversion rates.

Implementation partners1

Lutech

Sources & evidence1

Groundedness: 5/5

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

Metrovacesa Intelligent Assistant (MiA) Conversational AI for Real Estate Lead Qualification

Use case focus

Challenges

Solution

Impact

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