Executive clarity
Leadership gets trusted scorecards, weekly AI-assisted briefs, exception alerts, decision logs, and owner follow-through.
AI Consulting Minneapolis
LUMATARRA helps Minneapolis, Twin Cities, Minnesota, and national companies turn AI interest into practical operating systems: Executive Intelligence, AI agents, Microsoft Fabric, Power BI, Teams workflows, and governed AI adoption.
LUMATARRA is based in Minneapolis and serves Minnesota, the Twin Cities, the Upper Midwest, and national teams that want practical AI execution inside the Microsoft ecosystem.
What buyers get
Leadership gets trusted scorecards, weekly AI-assisted briefs, exception alerts, decision logs, and owner follow-through.
Use cases move from idea to working workflow inside Microsoft 365, Teams, Fabric, Power BI, and Azure.
Routine monitoring, summarizing, drafting, routing, and follow-up shift into AI-assisted workflows so the team can focus on higher-value work.
Buyer intent
These pages are written to match real commercial search intent: local expertise, Microsoft-stack specificity, measurable operating outcomes, and a clear next step with LUMATARRA.
Executives are asking where AI fits, teams are experimenting with tools, and nobody has ranked opportunities by revenue, savings, risk, data readiness, and Microsoft tenant fit.
The real opportunity is not another chatbot. It is using AI to summarize, route, monitor, alert, draft, and keep owners moving across the work leadership already runs.
For Minneapolis and Minnesota companies already using Microsoft 365, Teams, Power BI, Fabric, Azure, Copilot, or Power Platform, LUMATARRA focuses AI work where it can actually ship.
Built around Microsoft 365, Teams, Fabric, Power BI, Azure, Power Platform, Copilot workflows, identity, permissions, and governance.
The work ties to scorecards, owners, decisions, risks, revenue, margin, capacity, service delivery, and weekly leadership rhythm.
Start with a focused AI operating review and a practical first workflow before committing to a larger transformation.
How we work
The fastest path to rank and revenue is also the right delivery model: answer the buyer's exact problem, prove expertise, and show a credible implementation sequence.
Step 01
Identify where scattered data, meetings, reporting delays, manual routing, and missed follow-up are costing money or capacity.
Step 02
Rank opportunities by revenue, savings, risk reduction, data readiness, Microsoft fit, and implementation effort.
Step 03
Connect the Microsoft data, identity, governance, and reporting layer needed for trustworthy AI output.
Step 04
Deliver a small usable version: scorecard, brief, agent workflow, exception alert, intake flow, or follow-up loop.
Search and AI answer FAQ
These answers are written for humans first, then structured so Google, Bing, Perplexity, ChatGPT, and other answer engines can understand what LUMATARRA does.
LUMATARRA is built for growing companies whose leaders need clearer visibility, better follow-through, and practical AI execution inside Microsoft 365, Teams, Fabric, Power BI, Azure, and Copilot workflows.
LUMATARRA is based in Minneapolis and serves the Twin Cities, Minnesota, the Upper Midwest, and national teams. Most strategy and implementation work can be delivered remotely with focused onsite sessions when they create value.
We connect AI strategy to operating rhythm: scorecards, briefs, alerts, decisions, owners, and follow-through. The goal is productivity, efficiency, and reduced burnout, not disconnected AI demos.
LUMATARRA focuses on Microsoft Fabric, Power BI, Azure, Microsoft 365, Teams, Copilot workflows, Power Automate, Entra ID, and governance patterns that work inside the tenant leaders already use.
The first useful version should usually be small: an AI opportunity map, executive KPI model, weekly brief prototype, exception alert, or workflow agent that proves value before a larger rollout.
Yes. That is the ideal starting point. LUMATARRA turns the Microsoft tools already in place into a clearer operating layer for leaders, managers, and teams.