· AI · Laravel
How we add AI features to an existing Laravel app
A practical approach to adding AI to a Laravel product without rewriting it: where to start, what to keep out of the model, and how to avoid vendor lock-in.
Most businesses don’t need a new AI product. They need one or two useful AI features inside the app they already run. Here is the approach we use.
Start with one narrow job
“Add AI” is not a requirement. “Summarise each support ticket in two lines” or “draft a first reply from the customer’s history” is. Pick a task that is repetitive, low-risk, and easy to check. A good first feature saves time even when it is only right most of the time, because a person still reviews the result.
Keep the model at the edge
Your Laravel app already knows your data, permissions and business rules. Keep it that way. The model should receive only the information it needs for the task, and its answer should come back as structured data your code validates before using. Never let model output write to your database unchecked.
Run it in the background
AI calls are slow compared with a normal request. Put them on a queue, so the page responds instantly and the result appears when it is ready. Queues also give you retries and a natural place to log failures.
Don’t tie yourself to one provider
Wrap the model call in a small adapter class of your own. If a provider changes pricing, limits or quality, you change one class instead of the whole app. The same idea applies to vector search or anything else you add later.
Control cost from day one
Cache what you can, send less text, and log how many tokens each feature uses. Costs are easy to manage when you can see them, and hard to explain later when you can’t.
Plan for it being wrong
Show the user what the AI produced and let them edit or reject it. Record when that happens. Those corrections tell you where to improve the prompts.
Thinking about an AI feature for your product? Tell us what you’re trying to do and we’ll suggest the simplest approach.