Authors: Prof. Chetan Kumar V, Hardik Jain, Pranathi B H, Vikas R P, Srinidhi Prabhu M U
Abstract: The deployment of production-grade Multi-Agent Systems (MAS) from natural language specifications remains a significant challenge in software engineering, requiring so- phisticated role decomposition, reliable tool integration, exe- cutable code synthesis, and robust packaging with dependency management. This paper presents MindMeld, a novel tiered LLM orchestration framework that transforms natural language requirements into deployable, containerized multi-agent systems through a three-phase pipeline architecture. MindMeld introduces several key innovations: (1) a formal planning phase that generates machine-verifiable JSON agent specifications with explicit dependency graphs and interface con- tracts; (2) a closed-loop validation tier combining static analysis, dynamic runtime testing in isolated sandboxes, and iterative self-refinement based on structured error feedback; and (3) an automated integration phase that synthesizes orchestration logic, manages inter-agent communication, and produces containerized artifacts with complete dependency resolution. We conduct comprehensive evaluation on 47 diverse natural- language build requests spanning 8 task categories (data pro- cessing, API integration, document analysis, notification systems, workflow automation, content generation, monitoring, and multi- modal processing). Our results demonstrate that MindMeld achieves 78.7% end-to-end build success compared to 34.0% for single-pass generation baselines, with an average of 1.8 validation iterations per sub-agent. Ablation studies reveal that the planning phase contributes 23.4% improvement and the val- idation loop adds 21.3% improvement to overall success rates. A controlled user study with 24 participants shows 3.2× reduction in deployment time and 4.1/5.0 satisfaction scores. These results establish MindMeld as a practical framework for bridging the gap between natural language intent and production-ready multi- agent systems.
