Integrations & AI Workflows

Most businesses do not have a software problem. They have a software-that-does-not-talk-to-each-other problem. The data exists — it is in the store, the CRM, the inbox, the spreadsheet — and someone moves it between them by hand.

Integration work is unglamorous and it is usually where the fastest return is.

Connecting what you already use

APIs, webhooks, and scheduled syncs between the systems you have already paid for. Typical shapes:

• An order in one system creating a record in another, without a person retyping it
• A form submission that reaches the right inbox, the right CRM, and the right list — once, reliably
• Data pulled on a schedule so a report is current when someone opens it
• Two systems that disagree about the same customer, reconciled

The hard part is rarely the connection. It is what happens when it fails — a timeout, a rate limit, a record that already exists, a webhook delivered twice. Integrations that only work on the happy path create silent data loss, which is worse than no integration at all, because you trust it.

So the ones I build are explicit about failure: retries where retrying is safe, loud logs where it is not, and never an acknowledgement that something was delivered when it was not.

A worked example, on this site

This site runs several of these in production:

• The contact form sends through a transactional email API, validates on both sides, and never reports a false success — if delivery fails, it says so and shows a fallback address rather than swallowing your enquiry.
• The CMS commits directly to a GitHub repository through a GitHub App, which triggers a rebuild and a deploy. Editing a page in a browser produces a real commit with real history.
• Inbound email to this domain arrives by webhook, is signature-verified, and is forwarded on with the reply address rewritten so replies reach the person who wrote in, not a loop back to the server.

None of that is exotic. It is the ordinary plumbing that decides whether a system is pleasant or maddening to run.

MCP and agent-accessible systems

Model Context Protocol is how an AI assistant gets safe, structured access to a system rather than being handed screenshots and hope. If you want an assistant that can genuinely read from or act on your tools, this is the layer that makes it possible without exposing everything.

I build MCP servers and agent-facing endpoints for exactly this — scoped access, explicit permissions, and an audit trail of what was done.

AI where it earns its place

I use AI-assisted workflows heavily in my own work, and I have built an agentic system — Nexus OS, running on the Claude API across agency, SaaS, and daily-operations lanes — to test these patterns before they reach a client.

That experience is mostly why I am conservative about where AI belongs in a business:

Good fits. Summarising or classifying a pile of text nobody reads. Drafting a first version a human then edits. Extracting structure from messy input. Answering questions against documents you already own. Routing work to the right place.

Bad fits. Anything where a confident wrong answer costs money and nobody checks it. Decisions that need an audit trail you can defend. Replacing a judgement call that a person is actually good at. Anything added because it should be there rather than because it does something.

If AI is not the right tool for your problem, a scheduled script and a clear interface will outperform it, and I will say so.

Guardrails are part of the build

Working quickly with AI assistance only counts if it stays inside the security and governance boundaries your business needs. That means credentials that are scoped and rotatable, data that does not leave systems it should not, third-party access that is explicit and revocable, and a record of what ran.

Speed without those is not speed. It is debt with a short fuse.

Who this is for

Teams paying for good software that does not connect. Businesses where the same data is entered twice. Anyone who has been sold an AI product and cannot tell what it actually does.

I work with clients in Cincinnati and nationwide.

Got two systems that should talk and don't? Tell me what they are and what moves between them today. I reply within one business day.