What challenges did Interclínica face before AI implementation?

Interclínica faced challenges with manual, delayed data reporting relying on Excel, causing inefficiencies in resource allocation and clinical decision-making. The need was to create a centralized, real-time data platform with AI capabilities to provide instant and consistent KPI insights across a complex healthcare network.

What was the impact of the AI solution?

SofIA reduced information retrieval time from days to under ten minutes, reallocating 150 analyst hours every week to higher value tasks. Achieved 100% data-driven adoption in the pilot group, democratizing KPI access organization-wide. Enabled faster, accurate operational decisions improving patient care efficiency with significant time savings.

Source

GCP

Interclínica drives AI-powered healthcare analytics with Looker and BigQuery on Google Cloud

Use case typeHealthcare analyticsUpdated Jun 13, 2026

Interclínica, a Chile healthcare network, built an AI assistant "SofIA" using Looker's conversational analytics API and centralized real-time data in Google BigQuery to improve healthcare KPI accessibility and operational efficiency. SofIA enables natural language queries of healthcare KPIs, reducing data retrieval time from days to minutes and reallocating 150 analyst hours weekly. This transformation democratizes access to critical data across the organization, improving decision-making for patient care and resource allocation in clinics conducting 1 million consultations and 30,000 surgeries annually.

Organization: Interclínica
Industry: Healthcare
Location: Chile

Reported outcomes

100%

quantified impactAdoption & scale

Strategic outcomes

Better decisions & insightCentralized real-time KPI insightsNew product / capabilityBuilt natural-language analytics assistantEmployee experienceFreed analysts for higher-value workCustomer experience & trustDemocratized KPI access organization-wide

Primary read

Use case focus

Showing 3 of 3

1Conversational AI in Healthcare
2Healthcare Analytics
3Operational Efficiency

Interclínica faced challenges with manual, delayed data reporting relying on Excel, causing inefficiencies in resource allocation and clinical decision-making.
The need was to create a centralized, real-time data platform with AI capabilities to provide instant and consistent KPI insights across a complex healthcare network.

Implemented a data strategy incorporating Google BigQuery, Looker, Dataflow, and Cloud Composer to centralize healthcare KPIs.
Developed SofIA, an AI interface using Looker's conversational analytics API for intent-driven natural language data discovery to enhance user experience for clinicians and administrators.
Partnered with 3Cloud (corrected from Ucloud) to realize the AI-driven healthcare network vision.

Technologies

Google BigQuery Looker Dataflow Cloud Composer Looker conversational analytics API

SofIA reduced information retrieval time from days to under ten minutes, reallocating 150 analyst hours every week to higher value tasks.
Achieved 100% data-driven adoption in the pilot group, democratizing KPI access organization-wide.
Enabled faster, accurate operational decisions improving patient care efficiency with significant time savings.

Architecture

Interclínica centralized its healthcare KPIs using Google BigQuery combined with Dataflow and Cloud Composer pipelines, using Looker and conversational analytics API to build the AI-powered SofIA assistant enabling natural language KPI queries.

Implementation partners1

3Cloud

Sources & evidence1

Groundedness: 4/5

Primary source

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

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Customer evidence

Interclínica drives AI-powered healthcare analytics with Looker and BigQuery on Google Cloud

Use case focus

Challenges

Solution

Impact

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