Redefining enterprise challenges: legacy systems @ThiyaguPalanisamy & @Chandirasekar Thiagarajan faced a frustrating predicament – their crucial, opaque systems were deemed “black boxes,” hindering their ability to perform essential operations. These systems held the key to day-to-day operations but presented a daunting challenge to intervene and reverse engineer their functionality.
Using AI-assisted reverse engineering, these experts collaborated with a client to uncover the hidden underbelly of these systems – the underlying UI elements, binary data, and the intricate data lineage. The multi-lens approach they employed was a testament to their strategic thinking – starting from the visible artifacts (UI elements, binaries, and data lineage), they progressively enriched the data, delving into the nuances of logic, and maintaining the system’s integrity. The human validation phase remained central to ensuring accuracy and confidence in the extracted functionality. This journey from black box to blueprint revealed the transformative power of AI in modernizing decision-making and hastening the migration process.
A common enterprise problem: crucial legacy systems become “black
boxes”—key to operations but opaque and risky to touch. Thiyagu
Palanisamy and Chandirasekar Thiagarajan worked with a
client to use AI-assisted reverse engineering to reconstruct functional
specifications from UI elements, binaries, and data lineage to overcome
analysis paralysis. They developed a methodical “multi-lens”
approach—starting from visible artifacts, enriching incrementally,
triangulating logic, and always preserving lineage. Human validation
remains central to ensure accuracy and confidence in extracted
functionality. This engagement revealed that turning a system from black
box to blueprint empowers modernization decisions and accelerates
migration efforts.
