When enterprises modernize legacy systems, the hardest part is not swapping the technology stack — it is preserving the business logic buried inside decades-old code. We introduce AgentModernize, a multi-agent framework that tackles modernization as four distinct sub-problems, each handled by a specialized LLM-powered agent: business rule extraction, formal specification via Behavioral Specification Graphs (BSGs), code generation under behavioral contracts, and automated equivalence validation with a feedback loop for iterative correction. We evaluate the framework on a benchmark of seven synthetic telecom-domain legacy modernization scenarios spanning order processing, billing, provisioning, fault management, contracts, and account migration. AgentModernize achieves a mean behavioral equivalence rate of 40.6% — a 2.2× improvement over single-prompt LLM baselines (18.8%) — and reduces estimated manual remediation effort by 47.2%.
Sheikh Nazib Ahmed (2026) studied this question.