Generative AI consulting that ends in something running
We start from a real operational problem, pick the Microsoft AI that fits it, and build until it's in production with controls your security team signs off on.
Talk to an Expert →Pilots are easy. Production is the job.
Most organizations have an AI pilot. Far fewer have anything running that a business team depends on Monday morning. The demo skipped everything around the model: identity, data boundaries, monitoring, cost control, and someone who owns it after the person who built it moves on.
That's the work we do. Strategy that ends in a slide deck isn't worth paying for.
AI for users and AI for the business
We split generative AI work into two kinds, because they're bought, built, and measured differently.
AI for users
Tools that make each person faster, with guardrails around what they can reach.
AI for the business
Systems that change how a process runs, built on your own data.
How an engagement runs
- Find the friction. We start with the process that costs you the most time or money, who owns it, and what a good result looks like in numbers.
- Check the data. We confirm the data the use case needs exists, is clean enough, and can be reached safely. If it can't, we say so before you spend.
- Prove value fast. A focused proof of value on the real problem, with real data, in weeks rather than quarters.
- Build for production. Identity, access, evaluation, monitoring, and cost controls added before anyone depends on it.
- Stay on. Our Resident Senior Architects stay involved as you add use cases, so the second project builds on the first.
The planning side is covered in our guides to building an AI strategy and why AI projects that work start with friction, not features.
Our take: say no to AI that can't produce a number
Plenty of AI projects start with a product ("we want a chatbot") instead of a problem. We push back on that. If a use case can't clear a simple bar, a named owner and a measurable result, we'll tell you in scoping and point you at one that can.
AI tools let your team start more on their own, and we encourage it. We earn our keep on experience: knowing which architecture holds up, which data will break it, and what production takes.
Why CloudServus
- Azure Expert MSP, independently audited by Microsoft and held by fewer than 1% of partners
- Top 1% Microsoft Solutions Partner, with designations across Security, Data & AI, Infrastructure, Digital & App Innovation, and Modern Work
- 1,600+ engagements delivered, with Copilot, agent, and data platform work live in our pipeline now
- Senior by default. Named engineers who stay on your account, not a ticket queue.
Frequently asked questions about generative AI consulting
What does a generative AI consultant do?
A generative AI consultant helps you pick the right use cases, checks whether your data can support them, builds a proof of value, and takes the result into production with the right security and cost controls. On the Microsoft stack, that usually means some mix of Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, and Microsoft Fabric.
How do we choose the right first AI use case?
Start with friction, not features. Look for a process with clear inputs, a measurable cost, and a named owner, where the data already exists. A use case that can't show a number in a few weeks is a poor first choice, however exciting it sounds.
What's the difference between Copilot and building our own AI?
Microsoft 365 Copilot works across your Microsoft 365 data with no development. Custom agents and apps built on Microsoft Foundry do a specific job against specific systems, including ones Copilot can't reach. Most organizations end up running both.
Do we need our data cleaned up before we start?
For most use cases, yes, and finding out afterward is the expensive path. Checking data readiness first tells you which use cases are realistic now and which need foundation work. Our guide to assessing AI data readiness has the checklist.
Is AI work covered by Microsoft funding?
No. Microsoft funding applies to migration and modernization work. Copilot, governance, and AI build work sit outside it. If foundation work such as an Azure migration is on your roadmap, we'll tell you what qualifies and what doesn't.
Ready to move past the pilot?
No slide decks. Senior Microsoft engineers, real numbers, and a scope with an endpoint.
Talk to an Expert →