Most consultants will sell you AI. We'll tell you whether your data is ready for it. These are the engagements that get you there. Built on Microsoft Fabric, Power BI, and the rest of the Microsoft cloud, scaled to growing businesses, not enterprise budgets.
Every engagement starts with the same question: what is this data actually trying to tell you, and what's getting in the way of hearing it?
Here's the honest answer most consultants won't give you: most companies think they're ready for AI. Most aren't. The real value (the part that pays back in months, not years) usually comes from automation and integration. Connecting the systems you already own. Killing the manual work. Building the foundation AI can actually run on top of.
When we say AI, we usually mean automation and integration first. That sequence isn't a hedge. It's the math. Get those right and the AI work that follows, including AI agents that actually take action on your behalf, costs less, ships faster, and holds up in production.
Most data problems aren't data problems. They're foundation problems. Reports disagree because nobody owns the definitions. Dashboards take ten minutes to load because the model wasn't built for scale. AI is "exploring options" because there's no clean source to point it at.
We build the foundation properly: a Microsoft Fabric lakehouse using medallion architecture (bronze, silver, gold), source connectors to the systems your business actually runs on, and a semantic model that anyone in the company can query without breaking it.
Most executive dashboards die in their first quarter. They're either built for the wrong audience (engineers, not operators) or they answer questions no one is actually asking. The good ones share a few traits: they load instantly, the numbers tie back to what hits the bank account, and a board member can navigate them without a tutorial.
We design and build executive-grade reporting in Power BI: board packs, KPI dashboards, M&A target screens, operational scorecards. The kind of work that makes a CFO look prepared and gets a board chair off your back.
Every business has them: monthly close routines, invoice processing flows, onboarding checklists, weekly report assembly. They eat hours, depend on people remembering steps, and break when key staff leave.
We automate them using Power Automate, Azure Logic Apps, and (where appropriate) lightweight custom code. Not "rip and replace." Your tools stay where they are, but the work moves itself between them while you do something more valuable.
You bought the ERP. You bought the CRM. You bought the warehouse system, the e-commerce platform, the field service app. They all work, independently. The cost of them not talking is everywhere: duplicate entry, lagging dashboards, missed handoffs, and a finance team building bridges in spreadsheets at month-end.
We integrate these systems properly: APIs, event-driven pipelines, data syncs, master data management. The goal isn't elegance; it's a business where information flows where it needs to without anyone copy-pasting.
Boards are asking. Investors are asking. Your team is asking. The pressure to "have an AI strategy" is real. So is the pressure to not waste $500K on a pilot that goes nowhere because the underlying data wasn't ready.
This is a focused engagement: 2-4 weeks of structured assessment that answers three questions. Where would AI actually create value here? What infrastructure work has to happen first? Which pilot is worth running, and which one will burn cash? You get a written roadmap you can take to your board.
Once the foundation is right and the roadmap is set, we build. Microsoft Copilot Studio for internal copilots that know your business. Azure AI Foundry for custom models. Power BI Copilot for analytics. The work is less about choosing the model and more about the infrastructure around it: retrieval, evaluation, guardrails, change management.
The AI is the easy part. Everything that makes it actually work in production is the hard part. That's the part we build.
Copilots answer questions. Agents take actions. An agent qualifies the lead, drafts the outreach, sends the follow-up, updates the CRM, and pings a human only when something needs a real decision. The work that used to take an analyst now runs 24/7 with audit trails.
This is where most consultants build flashy demos and stop. The reason ours work in production is the same reason everything we build works in production: they're plugged into the foundation we already built. Clean data. Integrated systems. Real governance. An agent without that is just a chatbot with delusions of grandeur.
We build on Microsoft Copilot Studio for governed, low-code agents that live inside Teams and Microsoft 365, and on custom orchestration (Azure AI Foundry, Semantic Kernel) when the use case needs more horsepower or deeper integration with your existing stack.
Most engagements start with a short email exchange to find out what's actually slowing you down. No pitch deck, no proposal pressure. Just a conversation about your stack and where the friction is.