Modernizing a Legacy Investment Portfolio Management Platform with AI in Record-time

Executive Summary

The client operates as a boutique, investment portfolio management company. It has maintained a lean operational footprint for the last 40 years. It became the official platform of the National Association of Investors Corp and got recognition from PC Magazine, Forbes, Fortune, and AAII Computerized Investing. However, the platform rested on decades-old technology that Microsoft stopped supporting in 2010, putting a core piece of client’s business at risk. Client’s internal team did not have the specialized skillset needed to take on a system this old and this complex. Moreover, the platform’s tangled, undocumented logic had made past modernization attempts stall before they started. SSI took on the business problem the industry had largely written off as too risky to touch and solved it in record-time. 

A manual rewrite would have taken five years or more, even the skillset required was scarce and outdated. SSI modernized the entire platform in six months with smart pods (SSI hybrid AI team), cutting the timeline by roughly 90%.

The new platform after legacy data migration reached 95% accuracy on the first pass with every edge case preserved. The business now runs on a modern, fully supported platform, protecting the reputation it has built over four decades. 

 

THE BUSINESS CASE AND THE PROBLEM 

Legacy Platform & Lack of Skillset 

Every quarter, asset managers using the platform use to send clients reports built on numbers that must be right, from returns to tax lot detail. Those reports came out of a Performance Report Engine running on Visual FoxPro as the legacy language Microsoft stopped supporting in 2010. This caused major business problems: 

• No resources available with the legacy skillset to take on the rewrite
• Over 200,000 lines of undocumented complex investment algorithms, interdependent enough that even small changes risked complete system collapse.  
• A manual rewrite estimated at five years or more, with no guarantee of success due to above mentioned challenges.
• Industry benchmarks for modernizing a codebase of this size and age put the cost well into seven figures, with technical debt alone estimated to be half of the cost.

OUR INTERVENTION 

The Solution Blueprint for AI Migration  

SSI was able to take on these challenges due advance engineering capability, AI models, access to advance tools and skillset.  

SSI’s team responded with a three-stage blueprint instead of a single conversion pass: 

• Engineers manually converted a portion of the codebase to establish a verified translation pattern. 
• The team then surfaced decades of undocumented business rules buried inside the system using (technology/approach). 
• SSI assembled Smart Pod to carry out the entire modernization of the platform using Claude, rebuilding the entire legacy VFP based platform into a modern C# application.
  

SmartPods are SSI’s hybrid AI delivery teams: small teams of engineers paired with multiple AI agents working the codebase in parallel, each one converting files, cross-checking logic, and flagging anything uncertain for a human to review. Rather than one engineer working through the codebase file by file, this agentic approach let SSI move at the pace of the AI while keeping a person accountable for every decision it made.

 

The entire modernized codebase was verified against the original system. Any discrepancies detected were investigated and addressed. This also helped unearth business logic and calculation issues in the original codebase, which were corrected in the modernized codebase.  

Technology Benefits:  

Now the updated platform calculates the same figures its clients have relied on for years, on code that can be tested, typed, and read by the next developer who needs to. 

Domain knowledge is on demand. Business logic spanning more than twenty years is no longer locked inside undocumented codebase. Claude reads and explains any function in seconds, and new team members reach productivity faster than they could when the only documentation was the code itself. 

Surgical, low-risk changes. Because Claude Code reads the surrounding context before every edit, changes stay minimal and targeted. The merger annotation fix touched only two files, where prior manual attempts at similar fixes had carried a much wider blast radius. 

A blueprint that compounds. The custom migration skill the team built now captures the diagnosis playbook for this class of migration. Each new legacy modernization issue has been resolved faster than the one before. 

THE IMPACT 

What Changed for the Client 

• Brand new platform based on modern technology, interoperability and integration possibility with other modern platforms. 
• Newer user experience and interface opening client addressable market to current generations of users resulting in business growth and market expansion.  
• Cutting-edge, clean documented, maintainable code in a modern technology stack with mass industry adoption, future support and skillset availability.  
• The business was able to respond to their business need for modernizing the platform in a very short time and also on a feasible budget.  

Under the Hood 

Legacy Platform:	Visual FoxPro (VFP), .DBF files, crystal reports
Modernized Stack:	C#, .NET Core, MVVM architecture, SQL Server, Dev Express reporting tools
AI Tooling:	Smart Pods using Claude, Opus, Agentic Skills and Migration Workflow,