AI App Development in South Florida

AI that ships as working software: assistants, document automation, and features built into a real product. I build on Claude. When a plain SQL query answers the question better, I tell you that instead.

What AI development looks like in practice

• AI assistants: chat and task assistants grounded in your business's data, tuned for a specific job rather than generic answers.
• Document & data automation: reading intake forms, invoices, and reports; extracting what matters; routing it to the right system.
• Intelligent product features: search that understands intent, personalized insights, drafting and summarization built into your app.
• Workflow automation: replacing the copy-paste-review loop with a pipeline that does the routine 80% and flags the rest for a human.

Three AI products I have shipped

This is not theoretical. I have built and launched three AI products end to end: a study assistant that solves problems step by step and generates adaptive practice, a recovery app with journaling and insights, and a coding studio that plans features and tracks bugs alongside a developer. All three are on the work page, with screenshots. The experience shows up in the unglamorous parts. Grounding answers in your data, handling the case where the model is unsure, keeping the per-call cost predictable.

When AI is the wrong tool

Most businesses do not need a research project. They need one workflow made faster, or one feature customers will actually use. I build on Claude, add retrieval over your own records when the answer has to come from them, and put a person in the loop where the stakes call for it. If AI is the wrong tool, I say so and build the simpler system that works.

Data makes or breaks AI

AI features are only as good as the data underneath them. Fifteen years of database work sits behind every build I do, so the schemas, pipelines, and query plans can carry the intelligence layered on top. If the data needs work first, that is database consulting service.