This topic covers AI-enabled prescription‑renewal and medication‑management platforms—ranging from pilot projects to commercial solutions—that automate renewals, reconcile medication lists, surface drug interactions, and document clinician decisions. As of 2026, adoption is shaped by three interlocking needs: low‑code workflow integration with EHRs to speed deployment, clinical documentation tools that produce auditable, structured medication records, and regulatory‑compliance capabilities (privacy, provenance, explainability) required for clinician adoption and certification. Key tool categories and representative technologies from the provided toolset show how the stack is assembled: low‑code workflow platforms and enterprise assistants (IBM watsonx Assistant) enable no‑code and developer‑driven virtual agents to orchestrate renewal workflows; engineering frameworks (LangChain) and agent platforms provide the scaffolding to build, test, and run stateful LLM agents that interact with EHR APIs; web‑grounded answer engines (Perplexity AI) can supply citations and external evidence for clinical recommendations; decentralized and provenance‑focused infrastructures (Tensorplex Labs) and site audits like the Deci.ai → NVIDIA transition underscore growing interest in provenance, model optimization, and vendor consolidation for production deployment. Developer productivity and private deployment tools (GitHub Copilot, Tabnine, Windsurf, Tabby) accelerate integration, testing, and secure self‑hosted model workflows. Practical deployments emphasize human‑in‑the‑loop review, rigorous pilot studies, and audit trails to meet HIPAA/FDA expectations. Organizations evaluating solutions should weigh integration depth with EHRs, options for on‑prem or private hosting, model explainability and citation support, and the vendor’s pathway to clinical validation and regulatory compliance.