Gadoci Consulting has always operated across the full spectrum of AI transformation. We help organizations discover where AI fits, build the solutions that deliver on those opportunities, and run the long-term programs that make AI operational at scale. That work spans everything from use case discovery to custom AI engineering to full transformation partnerships.
But there's a gap in the market that none of those engagements are designed to fill. It's the gap between a team that has access to AI tools and a team that actually uses them.
We're adding a new way to work with us that targets that gap directly. We call it AI Embed.
The Concept
We take one of our people and put them with your team. Physically. On site, at the desk, for one and a half to three days. Our person comes in with deep, current fluency in the tools that are reshaping how knowledge work gets done: Claude, ChatGPT, Perplexity, and the broader ecosystem of AI capabilities that most teams have heard about but haven't integrated into their actual workflows.
The engagement isn't a presentation and it isn't a workshop. It's an immersion. Our person sits with your people, learns how they work, and then builds with them. Real tasks, real workflows, real output. By the time we leave, your team isn't just aware of what AI can do. They're doing it. On their own work, with tools configured for their specific needs, using workflows they helped build and now own.
Why This Exists
We spend every day inside these tools. Not evaluating them, not reading about them. Using them, building with them, pushing them into workflows across every function you can name. That's what Gadoci Consulting does. Our team lives on the cutting edge of how AI actually gets applied to real work.
And the cutting edge right now is moving fast. The Claude ecosystem in particular has evolved into something that looks less like a chatbot and more like an operating system for knowledge work. Skills, plugins, connectors, agentic workflows. These aren't future concepts. They're shipping now, and they're changing what's possible for a knowledge worker on a Tuesday afternoon. Other platforms will get there. OpenAI is investing heavily, and the broader ecosystem is converging on a similar vision. But Claude is where the future of AI-augmented work is most visible today, and understanding how to build inside that ecosystem is a meaningful advantage for any team that gets there early.
That daily fluency, across Claude and the broader set of tools, is the thing that's hard to transfer in a traditional engagement format. You can teach someone the mechanics of a tool in an afternoon. But showing them how it fits into the way they specifically work, how it handles the report they build every Monday, how it accelerates the analysis they run before every board meeting, how it changes the way they draft and edit and communicate, that requires sitting next to them and doing the work together.
AI Embed takes the operational knowledge our team carries every day and transfers it directly to yours. Not through slides or documentation, but through side-by-side work on the things your team actually does.
What Happens During an Embed
Our person shows up and starts by understanding the work. Not the org chart, not the technology stack. The work. What does this person or team spend their time on? Where are the manual steps? Where is the repetitive effort? Where are the bottlenecks that have become invisible because they've been there so long?
From there, we start building. We match tools to tasks. We create prompts, workflows, and configurations that are tailored to how your people operate. We don't come in with a predetermined toolkit or a one-size-fits-all curriculum. A finance team reconciling data across systems needs something completely different from a marketing team managing content production, and both look nothing like an engineering team doing code review and documentation. The tool selection and the approach happen in real time, based on what we see.
By the end of the engagement, your team has more than knowledge. They have working tools embedded in their actual workflows, habits that are already forming, and the confidence that comes from having built something real with their own hands. The people who go through an embed come out changed. Not because they attended something, but because they built something.
How It Fits With Everything Else We Do
AI Embed is a different kind of engagement from our other offerings, and it solves a different problem.
Use case discovery is about identifying where AI can create value across an organization. Point solutions are about building specific workflow automations. Full transformation is about operating AI at enterprise scale over time. Those are all strategic and architectural in nature.
AI Embed is purely about people. Take an existing team doing existing work and make them dramatically more capable by getting AI into their hands and their habits. The work doesn't change. The people do.
You can explore all of our engagement types here.
Who This Is For
Department heads, VPs, or operational leaders who know their teams should be getting more from AI but haven't been able to make it stick. The kind of leader who has already invested in licenses and maybe even sent people to a session or two, but the day-to-day hasn't shifted the way they expected.
The problem isn't the tools and it isn't the people. It's that nobody has sat with your team and closed the gap between the tool and the work. That's exactly what AI Embed does.