Microsoft Copilot consulting that ends with an agent the whole firm actually uses.
Your team can demo a Copilot Studio agent in an afternoon. Wiring it to your firm’s own data, publishing it to Teams and Microsoft 365, and getting every partner and analyst to change how they work — that is the real job. We advise, build, and run it as your AI operating partner.
Official services partner of the platforms defining AI
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Anthropic
Most Copilot projects stall between the demo and the rollout.
From a working session with a professional-services firm — an executive-compensation consultancy whose co-founder writes his own requirements docs and already builds with AI: one session, a custom connector wired to the firm’s own API, a Copilot Studio agent answering test questions. Then the real question landed: “Is there a way you can do this for the whole firm?”
The demo works; the rollout doesn’t
Building the agent is the easy afternoon. Getting it published to Teams and Microsoft 365 Copilot, with the right Azure permissions on the company tenant, is where DIY AI projects sit for weeks.
The build experience fights you
In the buyer’s words: “It’s not very smooth.” Publish a change and, in his experience with Copilot and Microsoft generally, you “check it the next day.” Propagation delays turn AI iteration into mailing letters.
Your data lives behind your own API
The agent is only useful if it can read the firm’s own numbers — the comp data, the client files, the news feeds. That means a custom connector built from an OpenAPI definition, API-key auth, attached to the agent as a tool — not a drag-and-drop template.
Personal environment vs. company tenant
An agent built in a personal environment is invisible to the org. Firm-wide publishing needs Azure permissions on the company tenant and the right internal/external visibility settings — one wrong checkbox and the AI rollout silently never happens.
Adoption is a change-management job
Even a perfectly wired agent fails if nobody changes how they work. Partners and analysts need training, prompt guides, and a reason to trust the AI’s answer over the spreadsheet they have used for a decade.
The roadmap doesn’t wait
Earnings summaries, client news, competitor market intelligence, a news detection engine — the AI wish-list keeps growing while the first agent sits unpublished in a test environment.
An AI agent nobody can open still bills you every month.
Licenses are live, the demo impressed the partners, and the roadmap is stalled on tenant settings and publish queues. Your numbers will differ — the first engagement puts figures on yours before anything else gets built.
From an anonymized Copilot-setup working session with a professional-services firm — an executive-compensation consultancy rolling AI out across its own tenant
Power Platform consultants who wire the build and run the rollout.
Three steps, fixed order — the same sequence every org-wide AI rollout needs. You don’t learn Copilot Studio the hard way; we do this for a living.
- 01
Wire your data into Copilot Studio
We build the custom connector from your API’s OpenAPI definition, handle the API-key auth properly, and attach it to the agent as a tool — the Copilot Studio implementation work that decides whether the agent knows your business or just the internet. If you run an MCP server, our MCP server consulting work wires it in the same way.
- 02
Publish to Teams and Microsoft 365
The build moves from a personal environment into your company tenant — Azure permissions, internal/external visibility, both channels published and propagation verified. The AI agent shows up where your people already work, for everyone, not just the person who built it.
- 03
Run adoption like a project
Change management is the real deliverable: training sessions, prompt guides, named owners, and a feedback loop that turns analyst complaints into connector fixes. Then the AI roadmap — earnings summaries, client news, market intelligence — finally has a foundation to stand on.
Power Platform consulting that ends with an agent in Teams — not a roadmap deck.
Microsoft sells you the licenses; tutorials get you a demo. We are an AI operating partner: the team that advises on what to build is the team that wires the connector, publishes the agent, and stays until your people actually use it. Copilot consulting, to us, means the whole job — build, rollout, adoption — not the first third of it.
Two boundaries, plainly. If the agent should live outside the Microsoft stack — model-agnostic, wired into your own product — that is our AI agent development work, a different engagement. And if the real question is keeping AI entirely inside your own security perimeter, that is our on-premise AI story. This page owns one job: making Microsoft Copilot work for a whole firm.
Is there a way that you can do this for the whole firm?
Led by Peter Enestrom.
Copilot Studio, Teams rollout, and other questions.
Straight answers, before you book anything.
The whole job: deciding what the agent should do, building it in Copilot Studio, wiring it to your firm’s data, publishing it to Teams and Microsoft 365 Copilot, and driving adoption across the org. One disambiguation up front: we mean Microsoft 365 Copilot and Copilot Studio — the AI assistant your whole firm can use — not GitHub Copilot for developers.
Yes — that is exactly the setup we wire. Your API’s OpenAPI definition becomes a custom connector with proper API-key auth, attached to the agent as a tool it can call. If your engineers built an MCP server instead, our MCP server consulting work connects it to Copilot Studio the same way. Either route ends with an AI agent that answers from your data, not the public internet.
Yes — most Copilot rollouts need both. A Power Automate flow handles the actions around the agent (route this summary, file that answer, alert this partner), and a small Power Apps front end covers the cases a chat interface shouldn’t. It is all part of the same Power Platform development services engagement, not three separate projects.
Because the demo is the easy part. The stall is almost always the same three things: the agent lives in a personal environment instead of the company tenant, publishing to Teams and Microsoft 365 hits permissions and propagation delays, and nobody owns adoption. The AI worked; the rollout was never scoped. That seam — demo to org-wide — is the whole reason this service exists.
If your firm runs on Microsoft 365 and the goal is an AI assistant in Teams that reads your own data, this is the right page. If the agent should live inside your own product, or you need it model-agnostic across OpenAI, Anthropic, Gemini, and open models, that is our AI agent development work — a different engagement with a different stack. Unsure which you are? That is what the first call is for.
Everything, inside your tenant: the Copilot Studio agent, the custom connector to your API, the Power Automate flows around it, the permission and visibility configuration, and full documentation — plus a trained team and a named owner for the AI roadmap. Support stays available; dependency is not the model.
Start with one workflow.
Tell us where your team loses hours. We will come back with a straight answer on whether AI can help, what it would take, and what it would pay.