services / ai-integration.md
Add production-grade AI to your product — without a rewrite.
Most businesses do not need a new app to benefit from AI — they need the product they already have to get smarter. I integrate large language models into existing websites, web apps, and internal tools: assistants that actually know your business, agents that do real work, and automation that removes manual steps.
Everything ships with production discipline: your data stays under your control, actions require human approval where it matters, and features are tested with evals before customers see them.
Chat assistants grounded in your data (RAG). Assistants that answer from your documents, products, and knowledge base — accurate, current, and free of made-up answers.
Custom AI agents. Multi-step agents that use your tools and APIs to complete work — finding records, drafting documents, preparing reports — with one-tap human approval on anything important.
MCP servers. Model Context Protocol servers that connect AI assistants like Claude to your business systems safely, with permissions and audit in mind.
Semantic search & document processing. Search that understands meaning, plus extraction and classification pipelines for invoices, contracts, and forms.
Voice interfaces. Speech-to-text and text-to-speech features for hands-free workflows, on desktop and mobile.
Workflow automation. Scheduled jobs, webhooks, and AI-driven steps that move data between your systems without copy-paste.
Intro call. A free conversation about your goals, current stack, and constraints.
Scoped proposal. A fixed-price first milestone — often a working prototype on your real data.
Build & iterate. Short milestones with demos; your feedback shapes each round.
Launch & support. Production deploy, monitoring, and ongoing improvements as you grow.
Yes — that is most of what I do. AI features like chat assistants grounded in your own data (RAG), semantic search, document processing, and workflow automation can be integrated into your current stack without a rewrite. I typically work with Next.js/React front ends, Node.js back ends, and the Anthropic Claude or OpenAI APIs.
RAG means the AI retrieves relevant passages from your actual documents and data before answering, instead of relying on what the model remembers. It makes answers accurate and current, dramatically reduces hallucinations, and keeps your private data under your control.
By grounding answers in your data (RAG) rather than model memory, requiring human-in-the-loop confirmation for any action that writes or sends something, adding evals and guardrails before launch, and monitoring behavior in production. Your private data is never used to train models.
Every project is scoped and priced as fixed milestones, so you know the cost before work starts. A small business site, a custom dashboard, and an AI feature are very different sizes — the free intro call is where we narrow it down and I give you a concrete quote.
More answers on the full FAQ page.
// ready when you are
The intro call is free — you leave with a concrete plan and a quote, whatever you decide.