Reports exist, but trust does not
Teams still debate which number is correct, who owns the KPI or why Power BI does not match Excel.
Enterprise assessment
Turn reporting doubt into a practical BI roadmap.
A focused assessment maps the decisions, reports, KPIs, source systems, semantic models and workflows that shape trust before a BI, AI or data platform project starts.
When assessment helps
Use assessment when the next move is unclear.
It is useful when reporting exists but trust, ownership, speed or architecture still block decisions.
Source systems are scattered
ERP, CRM, finance, operations, files and APIs need a controlled path into governed reporting.
AI is requested before data is ready
NLQ, agents and assistants need a semantic layer, permissions and trusted definitions first.
Delivery needs a safe first release
The assessment identifies what should be fixed first and what can wait without slowing momentum.
Assessment path
Enough structure to decide what to build first.
The assessment stays focused on business value, technical feasibility and operational ownership.
Discovery workshop
We align on the decisions, reports, teams and constraints that matter most.
Current-state review
We review source systems, models, KPI definitions, refreshes, workflows and ownership.
Findings and recommendations
We separate urgent trust issues from improvements that can wait until later releases.
Roadmap
You get a practical first-release direction for BI, AI readiness or data platform work.
What we assess
The assessment follows the trust chain behind BI.
We look at the business meaning, data path and operating habits behind the reports people rely on.
KPI definitions and ownership
Which definitions are shared, which are local and who can explain the number when it is challenged.
Source systems and integration
Where the data comes from, how it refreshes and where manual steps still create risk.
Semantic model and governance
Whether Power BI, workflows and future AI use the same curated business logic.
Workflow and AI readiness
Where reporting should become action, and where AI would need better permissions, quality or context first.
What you receive
A practical view of what to fix first.
The output is not positioned as free consultancy. It is a structured starting point for deciding whether, where and how to invest.
Current-state findings
A concise summary of the reporting, data and workflow risks that create friction today.
Prioritized opportunities
What is worth improving first, what can wait and which quick wins are realistic.
Recommended next steps
A practical path toward BI delivery, AI readiness, platform modernization or workflow improvement.
Indicative roadmap
A first-release direction that can become a workshop, pilot or implementation plan.
Assessment variants
One framework, different starting points.
The same assessment pattern can support BI, AI readiness and data platform decisions without turning into a generic contact page.
BI assessment
Power BI, semantic models, KPI ownership, reporting trust and first-release planning.
Start BI assessmentAI readiness assessment
Semantic layer, permissions, data quality and use-case fit before NLQ or agents.
Check AI readinessData platform assessment
Azure, SQL, lakehouse, Databricks, Fabric and operating model decisions.
Map the platformWho should attend
Bring the people who own the decision and the data reality.
The most useful assessment includes business owners, reporting users and technical stakeholders in the same conversation.
Business leadership
People who need reliable reporting for performance, planning, operations or executive decisions.
Finance, controlling or operations
Teams that know where definitions, spreadsheets, approvals and manual follow-up create friction.
Data, BI and IT
People who understand the systems, models, integrations and governance constraints behind the reports.
Future solution owners
The team that will maintain, adopt or extend the BI, AI or workflow capability after delivery.
Typical outcomes
Less debate about data. Clearer next moves.
A good assessment should make the first useful release easier to defend and easier to start.
Trusted reporting direction
Definitions, ownership and semantic logic are clarified before reports multiply.
Platform decisions with context
Azure, SQL, lakehouse, Fabric or Databricks choices are connected to business maturity and operating needs.
Workflow opportunities
Manual reporting and follow-up steps become candidates for controlled workflow or write-back surfaces.
AI readiness guardrails
NLQ and agent ideas are checked against data quality, permissions and business context.
Related proof
Assessment themes show up in real delivery work.
These client stories show why trust, ownership and architecture matter before scaling BI and automation.
Reporting modernization
Business logic moved out of hidden files and scripts.
Discovery and documentation reduced key-person dependency before BI modernization.
Read client story Finance transformationGoverned reporting for business-critical finance work.
Senior delivery across reporting, workflow, governance and operational support.
Read client story Cloud modernizationMigration planning around the business processes behind the databases.
Platform modernization shaped by operational continuity and enterprise constraints.
Read client storyAssessment FAQ
What happens before delivery starts.
Do we need a perfect brief?
No. A few painful reports, systems and business questions are enough to start.
Is this technical or business-focused?
Both. BI fails when business definitions and technical architecture are separated.
What do we get at the end?
A prioritized view of risks, opportunities and a practical first delivery path.
Can this lead into delivery?
Yes. The roadmap can become a BI, AI readiness, data platform or workflow implementation plan.
Start the assessment
Bring the reporting problem before it becomes a project.
Send the report, KPI, workflow or platform decision that creates the most doubt. We will help turn it into a practical assessment path.