By Kaique Jesus do Nascimento — Head of AI Solutions

Everyone’s talking about adding AI to their products. But what if your system is already live, full of legacy code, circular dependencies, and controllers with 500 lines each? Can you still bring AI into that reality? Spoiler: yes, you can but it takes strategy.
Here are some ideas I’ve seen work in real-world projects:
Don’t try to “AI-ify” the entire system at once. Pick a process that’s repetitive, costly, or involves simple decision-making. Examples: ticket classification, automated reply suggestions, task prioritization, or anomaly detection.
You don’t have to bury AI deep inside your app’s core. Create an external layer like an API or microservice dedicated to handling AI logic. This keeps the system loosely coupled, easier to test, and prevents what I call “emotional attachment” to a single model.
It depends on your use case and budget. But generally speaking:
Your AI will fail. It will hallucinate. It will confuse things sometimes. That’s why you should always design a fallback, a traditional path or human validation step. This is crucial when AI directly impacts the user experience.

You can’t improve what you don’t measure. Track how AI affects your app’s performance and user experience. It’s not about “look how cool this is,” it’s about “did this create real value?” If not, tweak it or turn it off, no hard feelings.
Integrating AI isn’t just about technology. It’s about understanding context, users, and product lifecycle. When done right, AI doesn’t replace, it enhances.
Ready to put real intelligence into artificial intelligence?