The problem: technical debt with no map

An industry non-profit was stuck. Over a decade of custom .NET code had accumulated around a legacy membership platform, undocumented, tightly coupled, and increasingly expensive to maintain. Modernization was the goal. Clarity was the problem.

The organization had been trying to understand its own codebase for years. A long-running manual discovery effort had produced little more than frustration. Without a clear picture of the workflows, business rules, and dependencies buried in the code, the team could not confidently plan a migration to AWS, let alone execute one.

The stakes were real: rising on-premises support costs, a vendor platform that no longer fit their needs, and a modernization initiative that kept stalling at the starting line.

The core challenges were painful and familiar to anyone who has inherited legacy systems:

They needed a faster path to clarity, and the right partners to get them there.

The partnership: Lexico Consulting + Mechanized AI + AWS

To tackle this challenge, the client engaged Lexico Consulting, a full-service business transformation consultancy that specializes in guiding organizations through exactly this kind of complex technology and operational change. Lexico brought the transformation strategy, stakeholder alignment, and program leadership, ensuring the engagement was anchored to real business outcomes, not just technical deliverables.

To accelerate the discovery and analysis phase, Lexico partnered with Mechanized AI, deploying mAI Modernize CodeMap inside the client's AWS environment. At the heart of CodeMap is Mechanized AI's advanced multi-agent framework, a coordinated system of specialized AI agents that collaborate to analyze, interpret, and document code at a depth and speed no single model or manual team can match. Rather than assigning another team of developers to read through 1.2 million lines of code by hand, this multi-agent architecture ingested the entire codebase automatically and orchestrated end-to-end discovery from structure mapping through business rules extraction.

CodeMap is architected and deployed natively on AWS, leveraging core services such as Amazon Bedrock for foundation model inference, Amazon S3 for scalable artifact and codebase storage, and AWS Lambda for event-driven orchestration of its multi-agent pipeline, among other services. This cloud-native architecture means CodeMap deploys directly into a client's own AWS environment with no data leaving their security boundary, while scaling elastically to handle codebases of any size.

Together, the three firms brought what neither could deliver alone: the business transformation expertise to frame the right questions, and the AI-powered multi-agent tooling to answer them at speed.

The solution: multi-agent intelligence at machine speed

In three days, CodeMap's multi-agent framework delivered what months of manual effort could not. Each specialized agent tackled a different dimension of the codebase, including structural analysis, dependency mapping, business rule extraction, and documentation generation, while a coordinating layer synthesized their findings into a unified, navigable picture of the entire platform.

What CodeMap produced

• A system-level summary giving architects and leadership a bird's-eye view of the entire platform.
• Feature-level documentation tailored separately for developers, architects, and business stakeholders.
• File-level breakdowns with functional descriptions, activity diagrams, data flow diagrams, and sequence diagrams.
• Extracted business rules translated into plain language, no code reading required.
• Visual system maps showing structure, workflows, and dependencies.
• A chat interface for on-demand interrogation of the codebase.

That last point deserves emphasis: teams could ask questions about the code and get contextual answers, turning an opaque legacy system into something they could actually navigate. Because the multi-agent framework handles the full pipeline from raw code ingestion through business-language output, end-to-end business rules extraction happened automatically, with no handoffs, no manual interpretation layers, and no gaps between technical analysis and business understanding.

Lexico's consultants used these outputs to rapidly align technical findings with business priorities, accelerating decisions that had previously been impossible to make with confidence.

The results: clarity that unlocked motion

The impact was not just speed. It was confidence.

With CodeMap's multi-agent output in hand and Lexico driving the modernization roadmap, the client finally had the foundation they needed to make informed decisions about scope, architecture, and migration sequencing. The uncertainty that had frozen their modernization effort was gone.

What changed

• Years of stalled discovery compressed into 3 days.
• Full visibility into custom workflows and system behavior.
• Complete, end-to-end business rules extraction, from embedded code logic to plain-language documentation, powered by the multi-agent framework.
• De-risked migration planning with data-driven scope and dependency mapping.
• Immediate momentum into the next phase, using CodeGen to re-architect and migrate workflows to AWS.

The results: measured against what manual would have cost

Every KPI below is benchmarked against what this work would have cost using traditional manual methods.

KPI 1: Time to production-ready delivery, 4 weeks

A traditional manual rewrite of an 83K-line application of this complexity, with full discovery, conversion, testing, and validation, would have consumed 3-5 months of calendar time. Mechanized AI's multi-agent framework compressed the entire lifecycle from legacy code to production-ready application into four weeks.

‍Baseline: 3-5 months for manual rewrite, industry standard for 83K LoC. Result: 4 weeks, end-to-end, from discovery through production-ready code.

The takeaway: you cannot modernize what you cannot see

Legacy modernization projects do not stall because organizations lack ambition or budget. They stall because the codebase itself is a black box, and because teams lack both the tools to illuminate it and the strategic framework to act on what they find.

This engagement worked because the solution addressed both sides of that problem. Lexico provided the transformation expertise and outcome assurance to keep the effort aligned to business needs. CodeMap, powered by Mechanized AI's advanced multi-agent framework, provided the AI-driven analysis to eliminate technical fog, delivering end-to-end code discovery and business rules extraction that no manual process could replicate. Together, they turned a stalled initiative into an active migration.

For organizations carrying years of technical debt, that combination, strategic transformation leadership paired with multi-agent AI-powered discovery, can be the difference between a modernization effort that moves and one that does not.

Facing a legacy codebase that is slowing your cloud migration? Mechanized AI and Lexico Consulting work together to help organizations move from confusion to clarity, fast. Let us talk about what is possible for your team.

About the partners

Mechanized AI builds AI-powered tools for legacy application analysis and modernization. CodeMap and CodeGen, driven by an advanced multi-agent framework, are part of the mAI Modernize suite, purpose-built for teams navigating complex, undocumented codebases.
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TLexico Consulting is a full-service business transformation consultancy helping leaders architect and execute technology, business, and operational change.