And how does AI or machine learning even fit into this kind of process?
I’ve been thinking a lot about how companies deal with aging software systems. My team still relies on an app built more than 10 years ago, and while it “works,” it’s painfully slow and doesn’t integrate with newer tools. I’m curious how other businesses approach modernization. Do you simply rebuild from scratch, or are there smarter ways to update what already exists? And how does AI or machine learning even fit into this kind of process?
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That is a classic dilemma. With software over a decade old, patching it often costs more in the long run than modernization. You do not always need a total rebuild from scratch, but you do need a modern architecture to support API integrations.
As for AI, it is not just a feature you bolt on; it requires clean, accessible data that legacy apps rarely possess. To bridge that gap, you need a robust foundation first. I recommend looking at https://topdevs.org/services/web-development. Their custom web solutions focus specifically on transforming legacy systems into scalable, high-performance platforms that are actually ready for AI integration.