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CASE STUDY

Okeiro

AI-enabled value-based care analytics platform linking clinical outcomes with operational and financial performance.

Industry Healthcare / Value-Based Care / Health Analytics
Solution AI-Driven Value-Based Care Analytics
Engagement 6 Months
Services AI & Full Stack Development
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Okeiro

Client Context

Okeiro is a France-based healthcare analytics and precision medicine company that leverages artificial intelligence to support value-based care and clinical outcome prediction. Its platform aggregates clinical, operational, and patient data to generate risk-stratified insights that guide care teams toward better quality results and cost-effective care delivery.

In 2025, Okeiro raised €10M in Series A funding to expand its deployment in hospitals and international markets, reflecting investor confidence in its clinically validated predictive models and its application in complex chronic disease management and post-transplant monitoring.

AI Clinical & Operational Analytics
Value-Based Care Enablement
Precision Medicine & Predictive Models

The Challenge

Develop a scalable analytics platform capable of ingesting diverse clinical, operational, and patient-reported data; delivering reliable outcome predictions and risk stratification; and providing actionable insights that help providers optimize care quality and control costs in value-based care arrangements.

Our Solution

We built an AI-powered analytics framework that unifies clinical and operational data, extracts meaningful features, trains outcome and risk models, and delivers real-time dashboards and alerts. The system provided care teams with precise predictive scores and actionable insights tied to pathways, cost drivers, and patient outcomes.

Data Ingestion & Normalization

Secure pipelines consolidating EHR, operational, and patient feedback inputs.

Outcome & Risk Prediction Models

ML models trained to estimate outcomes and identify high-risk patients.

Real-Time Analytics & Dashboards

Visual reporting tools and APIs for clinical and operational decision-making.

Continuous Retraining & Monitoring

Feedback loops and model updates to enhance accuracy and trustworthiness.

How We Delivered

1

Discovery & Alignment

Mapped care pathways, clinical outcomes, and data touchpoints to define metrics and success factors.

2

Architecture & Planning

Designed scalable, compliant data and model infrastructure.

3

Engineering & Integration

Built data pipelines, model training workflows, inference services, and dashboard components.

4

Testing & Validation

Tested model integrity, analytic accuracy, and integration with provider workflows.

5

Deployment & Support

Deployed analytics services, monitored outcomes, and refined features based on stakeholder feedback.

Outcomes Delivered

32% Improvement in Risk Stratification Accuracy

Predictive models enhanced identification of high-risk patient cohorts across complex care pathways.

25% Reduction in Cost per Patient Episode

Analytics-driven insights enabled providers to proactively manage cost drivers and improve operational efficiency.

45% Faster Clinical Decision Support

Real-time dashboards and predictive scoring accelerated care team response times.

99.9% Platform Availability

High-availability analytics infrastructure supported growing hospital deployments and international scale.

Related Capabilities

Healthcare Consulting Generative AI Development Healthcare App Development Cloud Application Development

Facing a Similar Challenge?

If you’re building an AI-enabled analytics platform for value-based care and clinical performance optimization, we can help architect, build, and deploy it.

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