Applied AI
AI woven into your business where it earns its place: image identification and review, workflow automation, assistants that answer from your own content, and connections that let AI work with your systems. Practical, not trendy.
Applied AI · MCP Integration
Connect AI to the systems your business actually runs on.
An AI assistant is only as useful as what it can reach. The Model Context Protocol (MCP) is how you give one safe, structured access to your tools, your data and your workflows, instead of copying and pasting between a chat window and the software where the work really happens.
Talk through an integrationIn plain language
What MCP is, without the jargon.
Most AI tools live in a box. They can talk, but they can’t do. They can’t look up a customer record, update a ticket, check inventory or pull a report, because they have no safe way to reach the systems that hold that information.
MCP is an open standard that solves exactly this. Think of it as a universal adapter between an AI assistant and your business software: a consistent, secure way for the AI to request information and take actions in the tools you already use. Instead of a one-off, brittle hack for every connection, MCP gives you a clean, maintainable way to let AI work with your systems, with you deciding exactly what it’s allowed to see and do.
Because it’s an open standard rather than one vendor’s proprietary trick, building on MCP fits how we work: no lock-in, standard tooling, and something your team or anyone else can maintain later.
Why it matters now
The difference between an AI that talks and an AI that helps.
An assistant that can only answer from a document is useful. An assistant that can check the live system, take the next action and hand back the result is a different kind of tool. It stops being a clever search box and becomes part of how the work gets done.
That’s the shift MCP enables. Because the standard is young, most organizations haven’t built on it yet. Getting it right early, with the right boundaries, security and judgment about what to automate, is an advantage while most of your competitors are still pasting prompts into a chat window.
What we build
How we help.
Connect AI to your existing tools
MCP integrations that let an assistant work with the systems you already run, such as CRMs, databases, internal tools and content systems, with access scoped to exactly what it should touch.
Build custom MCP servers
When a tool or data source has no off-the-shelf connector, we build the MCP server that exposes it safely, so your AI can use it like any other capability.
Design the guardrails
MCP isn’t about handing AI the keys to everything. We design what the assistant can read, what it can change, and what always needs a human, so automation stays safe and you stay in control.
Honest framing
When MCP is the right call, and when it isn’t.
MCP is powerful when you want AI to genuinely interact with your systems. It’s overkill when all you need is an assistant that answers from a set of documents. That’s a retrieval problem, and we’d point you to our conversational AI work instead. And it’s the wrong tool entirely when a plain integration with no AI in the loop would do the job more reliably.
We build all three, so we’ll steer you to whichever actually fits. The goal is the result, not the acronym.
Related services
Often part of the same project.
Conversational AI & Chatbots
Assistants that answer from your own content (benefits, documentation, policies, product data), grounded in your material instead of made up.
Integrations & APIs
The glue that connects your systems, getting data where it needs to go, reliably, between the tools your business already depends on.
Let’s work together
Want to see what AI could do with access to your systems?
Tell us what you’re running and what you wish AI could do with it. We’ll tell you whether MCP is the path, and how we’d build it safely.