This topic examines the AI platforms and tool categories that power personalized healthcare and integrated pharmacy services—focusing on secure data infrastructure, governance, clinical documentation, regulatory compliance, and patient-facing coaching. As of 2026, healthcare organizations are combining large multimodal models, agent frameworks, and low-code deployment platforms to automate medication reconciliation, support e‑prescribing workflows, generate structured clinical notes, and deliver personalized adherence coaching. Key tools and roles: LangChain provides engineering frameworks and stateful agent primitives for building, testing, and deploying reliable LLM agents that can orchestrate clinical and pharmacy workflows. Claude and Google Gemini serve as conversational and multimodal backbone models for clinical summarization, patient messaging, and decision support. StackAI and similar no-code/low-code platforms enable rapid enterprise deployment and governance of AI agents across care teams. Notion and PDF.ai help ingest, organize, and query clinical guidelines, formularies, and PDF records to make referenceable knowledge available to agents. Lingloop illustrates AI health coaching focused on personalized communication and behavior change support. Relevance and risks: Increased model capability and tighter EHR integrations make AI-driven personalization and pharmacy automation practical, but raise urgent needs for data governance, auditability, explainability, and regulatory compliance (HIPAA, FDA SaMD guidance). Effective solutions combine robust AI data platforms, security and governance tooling, clinical documentation automation, and validated coaching systems to reduce medication errors, improve adherence, and streamline clinician workflows. This overview helps clinical leaders and technical buyers compare platform capabilities and map them to operational needs—data integration, compliance, agent reliability, and patient-centered coaching—when building integrated healthcare and pharmacy services.