AI consulting on Microsoft 365 and Azure
AI & Automation
For organizations with Microsoft 365 and Azure in place and AI arriving faster than the rules for it.
We help you decide which AI to fund and set the guardrails first. Then we set up Copilot, drive adoption with a champions community, and build the AI solutions and automations that give people real time back.
Which service do you need?
- 01Decide
AI Strategy & Roadmap
Decide which AI to fund, under what controls, with an approved portfolio and a 90-day plan.
- 02Govern
AI Governance
An AI inventory, risk tiers, policies, and enforcement that let low-risk work move and stop high-risk mistakes.
- 03Secure
AI Security for Copilot and Agents
Threat modeling, data protection, and detection for Copilot, agents, and AI apps.
- 04Adopt
Microsoft 365 Copilot Adoption and Agents
Copilot set up and adopted, then agents and assistants built on your own documents, with a person approving what goes out.
- 05Build and run
Azure AI Platform and Operations
The Azure foundation custom AI runs on, and the release gates, monitoring, cost alerts, and tested recovery that keep it working.
- 06Prepare the data
Data Platform and Microsoft Fabric
Data ready for reporting and AI: a Fabric foundation, Power BI people trust, and data products with owners.
Questions we get
We have AI pilots and no plan. Which service do we need?
AI Strategy & Roadmap. It decides which uses of AI to fund, in what order, under what controls, and who owns each one. Where sponsors aren’t aligned yet, the smaller Executive AI Direction Sprint comes first.
People already use AI and nobody has set the rules. Where do we start?
AI Governance. It inventories the AI already in use, sorts each system into a risk tier, and writes the rules your people follow. AI Security for Copilot and Agents then models the threats and limits what each agent can reach.
We bought Copilot licenses and few people use them. Which service fits?
Microsoft 365 Copilot Adoption and Agents. The Copilot Readiness Assessment checks what Copilot could expose before rollout, then the adoption program builds use department by department with a champions community. Agents for repeatable work follow on the same content.
We plan to build our own AI apps or agents on Azure. What do we need?
Azure AI Platform and Operations first: the landing zones, networking, identity, and Microsoft Foundry structure the AI runs on, then release gates, monitoring, and cost alerts once it’s in production. Data Platform and Microsoft Fabric comes in when the AI needs data from your business systems.
Will we need to buy new tools?
Often not. We start with what you already license, such as Microsoft 365 Copilot Chat, Microsoft 365 Copilot, Copilot Studio, and Power Platform, and move to more customized options only when the evidence justifies it. Each recommendation includes a 'why not simpler?' check, and a process fix with no AI is a valid answer.
In what order do you do AI work?
Governance and guardrails come first: written rules for who may use AI, on what data, with whose approval, set before anything reaches your people. Then we set up the tools, drive adoption with a champions community, and build the AI solutions and automations that give people real time back. Measurement shows what is actually used. It's the proof.
Case studies
-
AI & Automation
Copilot adoption at a major New York City university, read more
A major New York City university had licensed Microsoft 365 Copilot, and almost nobody was using it.
-
AI & Automation
HR AI readiness assessment at a major New York City university, read more
The HR department at a major New York City university knew AI could help but had no shared way to decide where.
What’s new from Microsoft
Talk to us about AI & Automation
It starts with a 60-minute call. If we need more to scope it, a short questionnaire follows. Then a written proposal and statement of work. Once you approve, we begin with the Assess phase.