MyndYou
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MyndYou has 2 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 1 country.
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Hyperscaler mix
See whether MyndYou's cases are powered by Microsoft, AWS, GCP, or multiple providers.
How MyndYou builds AI
Build / Buy / Compose across this company's documented cases
1 of 2 cases classified (50%) · Compare all use-case types
Use case portfolio
Use case types at MyndYou
Conversational assistants leads with 1 of 2 documented cases; 2 distinct types appear across the visible portfolio.
Technology snapshot
What MyndYou uses across visible cases
AI Agents appears in 1 of 2 indexed cases; 9 named technologies are mentioned, led by BigQuery.
All Use Cases (2)
MyndYou Improves Patient Outcomes with AI Virtual Care Assistant Using Google Cloud
MyndYou developed 'Eleanor,' an AI-powered virtual care assistant, to improve patient engagement and chronic disease management amid US healthcare staffing shortages.Eleanor conducts complex clinical phone conversations, understanding both content and speech patterns to identify clinically relevant events and rank urgency.The solution uses Google Cloud Gemini large language models fine-tuned on clinical conversation data to accurately interpret patient responses.BigQuery analytics optimize call timing and maximize patient reach and engagement.HIPAA-compliant PaLM 2 large language model within Vertex AI is used for continuous service improvement without compromising patient data privacy.
MyndYou AI Virtual Care Assistant Improves Patient Outcomes with Vertex AI and Gemini
MyndYou developed 'Eleanor', an AI-powered virtual care assistant to address patient care staffing shortages and improve chronic disease management with automated patient outreach.Eleanor conducts clinical phone conversations, analyzing patient speech for clinical events and optimizing call timing using BigQuery analytics.MyndYou uses Vertex AI and Gemini, fine-tuning Gemini models for clinical accuracy and ensuring HIPAA compliance.The solution includes Speech-to-Text and Text-to-Speech APIs and uses Google Cloud Run and PaLM LLM for call data analysis and summarization.This implementation doubled successful screening appointment completions, improved patient engagement and trust, enabled regular check-ins for high-risk patients, and optimized healthcare provider workflows.
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