Objectives: This study evaluated the feasibility and performance of a multi-agent (MA) system designed to support early sepsis management in intensive care units. The system integrates three specialized agents—sepsis management, antibiotic recommendation, and guideline compliance—to provide evidence-based recommendations at T = 0 hours (before culture results), extending prior single-case findings across 10 diverse cases. Methods: The MA system was powered by Palmyra- Med 70B (selected for superior MedQA performance [average score, 85.9]) and compared with GPT-3.5 Turbo and GPT-4o mini (all at a temperature of 0.25). It used retrieval-augmented generation (RAG) with ChromaDB (2021 Surviving Sepsis Campaign, over 20 high-impact manuscripts [reviews published 2018–2025] on sepsis etiologies, and other relevant sources). Eight cases from the MIMIC-IV demo and two cases from the literature were formatted as vignettes. RAG used the BAAI/bge-base-en-v1.5 embedding model with cosine similarity (threshold, 0.75) and top-5 chunks. Performance was assessed via TruLens (groundedness, approximately 0.62) and by two intensivists using a standardized questionnaire. Results: The system generated guideline-compliant recommendations (e.g., prompt surgical debridement plus meropenem and vancomycin for necrotizing fasciitis). Hallucinations occurred in three of 10 cases (e.g., “altered mental status”). Expert agreement was quantified by a Cohen kappa of 0.26. Programmatic and expert assessments showed negligible correlation. Conclusions In this exploratory study, the MA system shows preliminary promise for early sepsis support but requires human oversight to mitigate hallucinations. Code is available in GitHub; further validation is needed.