Back to blog
AI Companion for End-of-Life Care Conversations
United States
Project Overview
Strategy & Advisory
Governance & Risk
Agents
A healthcare firm sought to improve how patients engage in advance care planning and end-of-life conversations. Existing processes relied heavily on limited clinician time, resulting in delayed discussions, inconsistent documentation, and missed opportunities for patient-centered decision-making.
SFAI Labs partnered with executive, clinical, and product stakeholders to design an AI Product Strategy that balanced emotional sensitivity, regulatory compliance, and operational scalability. The goal was to enable patients to explore care preferences in a structured, supportive environment before clinical escalation.
Using our lab acceleration model, we designed a mobile-first, iPad-based solution supported by agentic AI systems and a privacy-first architecture. The platform guides patients through personalized, values-driven conversations while ensuring secure integration with healthcare infrastructure.
Within the engagement period, SFAI Labs delivered a production-ready strategy, system blueprint, and phased roadmap for deploying empathetic AI at scale in regulated clinical environments.
Key Takeaways
Trust enables adoption
Ethics drive design
Compliance enables scale
Empathy improves outcomes
Structure reduces risk
Challenge
Healthcare providers faced increasing pressure to deliver personalized, value-based care while managing limited clinical time. Advance care planning conversations were often delayed, incomplete, or inconsistent. Patients lacked accessible tools to explore their preferences independently, and providers lacked scalable systems to document and act on these insights.
Additionally, the sensitive nature of end-of-life discussions required strict safeguards around tone, data privacy, and regulatory compliance.
Strategy
SFAI Labs defined a patient-first, compliance-driven strategy centered on mobile accessibility, empathetic interaction, and agentic system design. We prioritized early deployment on iPad to accelerate validation, aligned with existing infrastructure, and structured the roadmap around multi-agent orchestration for context management and decision support.
The strategy emphasized HIPAA- and SOC-2-aligned architecture, human oversight, and progressive automation to ensure safety and reliability.
Solution
We designed an AI-powered advance care planning platform featuring:
Empathetic conversational agent for ACP guidance
Branching decision logic for personalized care paths
Multi-agent context and reasoning system
Secure Azure-hosted infrastructure
Structured data ingestion and validation pipelines
Compliance-ready audit and reporting framework
The system enables patients to explore values, preferences, and treatment goals while producing clinician-ready summaries and documentation.
Execution
Week 1–2: Clinical workflow analysis and compliance alignment
Week 3–4: Agentic system architecture and data design
Week 5–6: Conversational logic and empathy modeling
Week 7–8: Security, governance, and deployment planning
Week 9–10: Pilot readiness and institutional integration
Results
Validated mobile-first ACP workflow
Secure multi-agent architecture defined
Pilot-ready platform roadmap delivered
Business Value
The engagement enabled the client to modernize advance care planning while reducing clinician burden. Providers gained scalable tools for earlier patient engagement, improved documentation quality, and better alignment between patient preferences and care delivery. The solution also positioned the organization for value-based care initiatives and long-term cost reduction.
Why SFAI Labs
SFAI Labs combined deep AI systems expertise with healthcare compliance and ethical design principles. Our lab model enabled rapid validation without compromising safety, privacy, or patient trust—delivering a foundation for responsible AI adoption in sensitive clinical contexts.
