Not a demo that impresses for a week, but AI wired into your real software — a chatbot that answers from your own data, a feature that drafts or summarises, a workflow that stops needing a human for the boring part. I connect the OpenAI and Claude APIs into the apps you already run, and make them reliable. Remote, worldwide.
The value isn't the model — it's how well it's wired into your data, your app and your workflow. Here's the kind of AI integration I build, with the plumbing done properly.
Support and internal assistants that answer in your voice — with guardrails, so they help customers instead of inventing answers.
Retrieval over your documents, database or knowledge base (RAG) so the AI responds from your content, with sources — not just the internet.
Reading invoices, contracts, forms and emails — pulling out the structured data your systems need, at a fraction of the manual time.
Drafting, classifying, summarising and routing — the repetitive text work that used to need a person, done as a reliable step in your process.
The AI feature built into your existing .NET or React app and its API — not a separate tool your team has to remember to use. See backend work →
Token and cost control, prompt-injection care, rate limits and graceful fallbacks — so the feature is safe to put in front of real users.
An AI feature is only useful if it's reliable, controllable and honest about what it doesn't know. Every build ships with that engineered in.
The hard part of an AI feature isn't calling the API — it's the data access, the app it lives in, and the reliability around it. That's ordinary engineering, and it's what I do.
What the AI should actually do, where it helps, and where a human still decides. We agree the scope honestly — including what's out.
Getting the AI access to the right content — your documents, database or knowledge base — cleanly and safely.
The prompts, retrieval and API layer, built into your app behind a clean interface, with previews as we go.
Guardrails, cost limits, safety and fallbacks — tested against the messy inputs real users will send.
Release it, watch how it behaves on real use, and refine the prompts and retrieval. See support options →
Related services that build the software an AI feature needs around it — the backend, the frontend and the data layer.
The ASP.NET Core API that calls the model, handles auth and keeps the AI feature reliable behind the scenes.
The chat and assistant UI your users actually interact with — streaming responses, history and a clean experience.
The data the AI retrieves from — modelled and indexed so retrieval is fast and answers stay grounded in your content.
Tell me what you want the AI to do and where it fits — a rough idea is enough. You'll get an honest take on whether AI is the right tool, an honest scope, and a clear quote.