Chapter 01 — Approach
Process. Data. Automation & AI. Run.
Automation and AI do not fix a broken process. They scale it. So we work in a fixed order: get the process and data ready, then build, then keep it running.
02 — Why the order matters
Automate first, and you scale the problem.
A flow built on an undefined process breaks on every exception. An agent reading duplicate, disconnected data gives confident wrong answers. A dashboard on top of both shows numbers nobody trusts.
Each step makes the next one safe. Process tells you what the data has to support. Clean data is what automation and AI can rely on. Run keeps both from drifting once people start depending on them.
03 — Order of operations
Process → Data → Automation & AI → Run
Process
We follow the work as it happens today, not as the org chart says it should. We name who owns each step, where work waits, and how exceptions are handled. Disagreements surface here, in a workshop, instead of later in a broken flow.
What you get
A documented process with named owners, agreed exception paths, and the decisions the system has to support.
Data
We find duplicate records, conflicting sources, and fields nobody maintains. We decide which system owns each record, design the Dataverse model, and plan the integrations and cleanup before anything is automated.
What you get
A data model, an integration plan, and a cleanup list, with an owner for every critical field.
Automation & AI
Now we configure Dynamics 365, build Power Platform apps and flows, and put Copilot and agents to work. We test against real exceptions and demonstrate working software in small increments, so the automation fits the process instead of fighting it.
What you get
Working Dynamics 365, Power Platform, and Copilot capabilities, tested against the cases that used to break.
Run
Processes change and data drifts. We stay on to support users, manage Microsoft releases, keep data quality in check, and work a visible backlog, so what we built keeps matching how the business runs.
What you get
Ongoing support, release management, a prioritized backlog, and regular licensing reviews.
04 — Principles
The rules we use to make delivery work.
Say what we see
If the process is not ready, or the data will not support what you want to build, we tell you before the build starts, not after.
Senior-led delivery
The people making architecture decisions stay close to configuration, testing, and your team.
AI-accelerated build
We use AI to speed up defined delivery tasks. A senior practitioner still reviews the work and owns the decision.
We stay after go-live
We handle support, releases, licensing, and the enhancement backlog after launch.
05 — Week to week
You see the work. You make the decisions.
We meet with the people who own the process. We demonstrate working software, record decisions, and call out blocked work.
You know what changed, what is next, and which decision we need from your team. We raise scope and data problems when they appear, not at the end.
Final chapter — Start
Let's talk about what's slowing your team down.
Tell us where work gets stuck, which systems are involved, and what needs to change. We will tell you whether we can help.