Unified data for better decisions.
We unify your data in Microsoft Fabric and Dataverse so that reports and AI work on the same information.
Microsoft Fabric
Dataverse
Azure SQLDo you recognize any of these situations?
These are the situations we see most often when a project starts. If any sounds familiar, let's talk.
Let's talkReports that do not add up
Each department reports different figures for the same KPI.
Data in silos
Information is scattered across systems that do not talk to each other.
AI without a foundation
AI projects stall because of data quality or access.
Dependence on IT
Every new report requires a request to IT.
Microsoft technology, chosen for your process.
Microsoft Fabric
Unified data platform: OneLake, shortcuts and mirroring, lakehouse, modeling and governed reporting.
When it fits: When you need a single enterprise data foundation for BI and AI.
Details at Microsoft ↗Power BI
self-service visualization and reporting.
When it fits: When departments need reliable, up-to-date dashboards.
Details at Microsoft ↗
Dataverse
The business database behind Power Platform and Dynamics 365.
When it fits: When business applications share a data model.
Details at Microsoft ↗
Azure SQL
Managed relational database on Azure.
When it fits: When you migrate or modernize existing databases.
Details at Microsoft ↗Azure Data Factory and Synapse
data integration and orchestration across systems.
When it fits: When data comes from ERP, CRM and external sources that need consolidating.
Details at Microsoft ↗Product icons and names are Microsoft trademarks and are used only to identify the products we implement.
Fusion teams and sprints.
Your power users and our team build together: prototype first, sprints with demos and governance rules that let you publish safely. Based on Microsoft's Power Platform adoption guidance and the Fabric adoption roadmap.
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We pick the right process and define the expected outcome.
Milestone · Backlog and metrics agreedWhat we do
- Workshop with the users who live the process today.
- Prioritization by value, effort and available data.
- Success metrics and solution owner defined.
- Environments, data policies (DLP) and starting licensing.
What you get
- Prioritized backlog.
- Agreed success metrics.
- Environment ready for prototyping.
AIAI in this phase
Analysis of the process and existing data to propose design alternatives.
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A prototype users try before the solution is built.
Milestone · Prototype validated with usersWhat we do
- Prototype in Power Apps, Power Automate or Power BI on representative data.
- Test sessions with users and immediate adjustments.
- Architecture decision: Dataverse, connectors, Fabric.
- Security and compliance validation of the prototype.
What you get
- Prototype validated by users.
- Final architecture and scope.
- Refined build estimate.
AIAI in this phase
Draft apps, flows and reports generated with Copilot from the process description.
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Your power users and our team build together, sprint by sprint.
Milestone · Sprint demoWhat we do
- Fusion team: power users (makers), W-IT developers and IT.
- Sprints with a demo at the end and a living backlog.
- ALM: development, test and production environments, with pipelines.
- Functional and performance testing on every increment.
What you get
- Usable increments every sprint.
- Living solution documentation.
- Makers trained during the build.
AIAI in this phase
AI-assisted formulas, expressions and tests, with automated quality review.
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We go live with digital guardrails: governance that enables rather than blocks.
Milestone · Governed go-liveWhat we do
- Publishing in managed environments with data policies.
- Security: roles, data access and compliance.
- Training and launch support.
- Usage telemetry from the start.
What you get
- Solution in production and governed.
- Trained users.
- Usage and adoption dashboard.
AIAI in this phase
Real usage measurement and early adoption alerts.
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We take the model to more processes with a Center of Excellence.
Milestone · Maturity reviewWhat we do
- Center of Excellence (CoE): standards, inventory and platform monitoring.
- Maker community and mentoring.
- Backlog of new apps, flows and reports ranked by value.
- Maturity assessment and improvement plan.
What you get
- CoE running with defined roles.
- Roadmap of new solutions.
- Measured maturity level.
AIAI in this phase
Detection of AI automation opportunities in processes already digitized.
Solutions Partner for Cloud & AI Platforms (Data & AI)
See Trust CenterShall we talk about your case?
Tell us what you have in mind and we will discuss your scenario, no strings attached.