AI strategy consulting
Microsoft Copilot Specialization · Microsoft Fabric Featured Partner · Databricks Partner
An honest AI partner knows when AI isn’t the answer.
An honest AI partner knows the difference between business problems that need AI, and business problems that don’t.
Most AI strategy work fails for two reasons: data that wasn’t ready to support intelligence, or intelligence applied to the wrong problem.
We solve both before any engineering starts. We work with you to identify your highest-value use cases, validate them through business and data discovery, and match each one to the right intelligence pattern (analytics, productivity AI, or AI engineering). Then we build the operating model to scale what’s working.
Where to start
Data intelligence
For teams with existing BI, Fabric, or Databricks investments who want to build AI on a data foundation they trust.
Agentic AI
For teams ready to build agents, or teams already grappling with agents running in their environment.
Productivity AI
For teams rolling out Microsoft 365 Copilot and extending it where Copilot alone isn’t the right answer.
Why Inviso for AI strategy
We recommend the right level of intelligence for the problem, not the most ambitious option that fits the brief.
Microsoft Copilot Specialization, Microsoft Fabric Featured Partner, and published Databricks Partner. Strategy backed by delivery depth on the platforms you’ll build on.
Proof, not promises: 87%+ Copilot adoption at Dark Matter Technologies and 5,500+ Copilot MAUs added across our book of business in the last 12 months.
Not sure whether your problem needs AI? Bring it to us. Book a free AI strategy session.
FAQs
How do we know which AI journey to start with?
You don’t have to know. That’s what our strategy sessions are for. We assess where you are (data maturity, Copilot footprint, agent activity) and map the right sequence. Most clients end up running more than one journey in parallel.
What if AI isn’t the right answer for our problem?
Then we’ll say so, and recommend what is. Plenty of business problems are better served by reporting, automation, or process fixes than by AI. Sometimes, applying the right level of intelligence to the right problem means no AI at all.
Do we need to fix our data before talking to you?
No. Come as you are. If discovery shows the data foundation isn’t ready, that becomes the first workstream. Most AI failures trace back to foundations that weren’t ready, so finding that out early is the strategy working, not failing.
What are the three delivery models?
Every engagement draws from one or more of: analytics & predictive intelligence (reporting, forecasting, decision support on trusted data), productivity AI & enablement (Copilot adoption and in-workflow assistance), and AI engineering & automation (intelligent applications, agents, and automated workflows on Azure AI Foundry).