Most products don't need to be rebuilt from scratch to use AI. They just need the right integration, wired in properly.

I add AI features to existing web applications. Chat interfaces, document processing, natural language search, automated data extraction, LLM-powered workflows. I've done this in production across multiple industries — fraud detection for a fintech platform with 200+ brokers, document automation cutting manual work by 70%, and a natural language to SQL engine for non-technical analysts.

I work with OpenAI, Gemini, AWS Textract, and RAG pipelines. I handle the integration, the prompt engineering, the API layer, and the UI that your users actually interact with.

You don't need a separate AI team. You need someone who can connect the dots between your product and the model.

AI feature scoped, built, and shipped into your existing codebase

Prompt engineering and model selection handled

API integration with error handling and rate limit management

UI for the feature (chat window, upload flow, results display, etc.)

Basic evals so you can tell if it's working correctly

Documentation on how the integration works and how to maintain it

1 week post-launch support

Discovery — I review your existing codebase and we agree on exactly what the AI feature needs to do

Model selection — I recommend the right model and approach for your use case and budget

Prototype — I build a working version you can test internally within the first week

Refinement — We tune the prompts and outputs based on real usage

Integration — Feature is merged into your main codebase, tested, deployed

Handover — Loom walkthrough of the integration so your team can maintain it