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Google > Case Studies > Genial Care Leverages Generative AI to Enhance Clinical Care for Children with Autism

Genial Care Leverages Generative AI to Enhance Clinical Care for Children with Autism

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Customer Company Size
Mid-size Company
Region
  • America
Country
  • Brazil
Product
  • Google Cloud
  • Vertex AI
  • BigQuery
  • Firebase
  • Google Kubernetes Engine
Tech Stack
  • Google Cloud
  • Vertex AI
  • BigQuery
  • Firebase
  • Google Kubernetes Engine
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Productivity Improvements
  • Customer Satisfaction
  • Digital Expertise
Technology Category
  • Analytics & Modeling - Machine Learning
  • Platform as a Service (PaaS) - Data Management Platforms
  • Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
  • Healthcare & Hospitals
  • Life Sciences
Applicable Functions
  • Business Operation
  • Quality Assurance
Use Cases
  • Predictive Maintenance
  • Remote Patient Monitoring
Services
  • Cloud Planning, Design & Implementation Services
  • Software Design & Engineering Services
  • System Integration
About The Customer
Genial Care is a healthcare network based in Sao Paulo, Brazil, specializing in innovative care for children with Autism Spectrum Disorder (ASD) and their families. The company is a Latin American reference in this field, aiming to help each child reach their full potential through personalized intervention. Genial Care combines advanced therapeutic models, educational support, and proprietary technology to enhance the quality of life and well-being of all individuals involved in the intervention process. The company is committed to constant monitoring of sessions with children, utilizing internally developed tools like the Clinical Panel to ensure comprehensive care.
The Challenge
Genial Care faced a significant challenge in scaling its operations due to the time-consuming process of recording medical records after each intervention session with children. The therapists were required to document every detail of the sessions, which was not only a requirement by the Health Councils but also essential for feeding the product to provide effective clinical recommendations for future sessions. As the number of cases grew, this process became increasingly costly and time-consuming, taking up to four days to complete. The company needed a solution to maintain the quality of records while reducing the manual workload of therapists.
The Solution
To address the challenge of time-consuming medical record documentation, Genial Care partnered with Google Cloud and participated in the Google for Startups program. The company developed a solution called LIAM, leveraging Vertex AI to automate the process of recording medical records. Therapists now record audio descriptions of sessions, which are processed by Vertex AI to convert them into text. This text is then used to create summaries and highlight key points, making it easier to track session progress. The integration of Google Cloud products, including Kubernetes, Firebase Analytics, and BigQuery, further optimized care and information management, allowing for greater agility and productivity.
Operational Impact
  • The use of Vertex AI has significantly reduced the cognitive load on therapists, allowing them to focus on important details of intervention sessions without worrying about specific formats.
  • The integration of Google Cloud products has enabled Genial Care to maintain high-quality records in compliance with Health Council regulations, while also providing analytical insights for decision-making.
  • The automation of medical record documentation has led to greater engagement from caregivers, who can now closely monitor the progress of the work being done.
  • Genial Care has achieved a stable and scalable product, with the ability to quickly prototype and validate solutions.
  • The company benefits from simple and intuitive cost management, maintaining financial control within the platform.
Quantitative Benefit
  • Reduction of working time from approximately 2 hours per day to 3 minutes per session.
  • Zero downtime in the last 4 years.

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