Niklas Hoeppener
Founder • Ariavor
- Four years in controlling
- Closing books and defending the numbers in them
- Then eleven years
- BI consulting across Europe
Decide Faster With Numbers You Can Defend.
We build the reporting layer your finance team runs on, one semantic model feeding both Power BI and Excel, so every entity consolidates the same way and a number means one thing wherever it is read. Your AI has to stand on that same model, which is why we start there.
- Microsoft Fabric
- Power BI
- Multi-entity consolidation
Why AI pilots stall
Your AI inherits whatever your numbers already mean.
Copilot licences, AI pilots and chatbot wrappers all work as advertised, and that is the problem. When revenue means three different things across your ERP, your CRM and a folder of spreadsheets, the assistant repeats all three with equal confidence, and leadership quietly stops trusting any of the answers. The fix is not more AI, it is the semantic model underneath it.
/01
No semantic layer
Nobody has told the AI how your business fits together. So it guesses, inferring relationships from table and column names, then reports the answer as confidently as a figure someone actually checked.
/02
No governed metrics
Two entities report the same revenue differently, both figures come from a dashboard, and both are correct under definitions that live in people’s heads rather than in a model. Every meeting opens with a reconciliation, and an assistant simply picks one.
/03
No stable foundation
A source system renames one field, and everything wired straight to it breaks, because no model sits in between to absorb the change. A dashboard at least goes blank, while an assistant carries on with whatever is left.
Not a bet: the direction of the platform
Microsoft just made the semantic layer foundational to AI.
Read the 2026 Fabric and Power BI releases together and they point one way: AI agents grounded in governed semantic models. That used to be our contrarian opinion. It is now the published roadmap of the tools you already pay for.
Fabric Data Agents
Ask your data, inside Microsoft 365
Data agents now publish into Microsoft 365 Copilot. But they only answer as well as the governed model they’re grounded in.
Fabric IQ
Governed context for every agent
Copilot Chat and Cowork now draw on Power BI semantic models directly, so answers stay grounded in trusted, curated data.
Agent Skills for Fabric
AI that authors on your model
Open-source skills let Claude and Copilot build reports and query semantic models. The results are only production-grade when the model is.
"AI-ready" models
Microsoft's own word, now
Copilot in Power BI recommends changes to make models "more AI-ready". That’s precisely the layer we’ve spent a decade building.
Every one of these capabilities assumes a clean, governed semantic model already exists. That’s the part they don’t build for you. It’s the part we do.
Foundation • Activation Sprint • Acceleration
Three services. One foundation that carries you from BI to AI.
These are the three ways to engage us, and most engagements start at Foundation. Some stay there and get exactly what they need. The ones that go further are the ones whose AI actually works, because the groundwork was already done.
01/03
FoundationStart hereMake your data AI-ready.
- Semantic modelling
- Microsoft Fabric
- DAX
- Data engineering
- Excel migration
The structural layer everything sits on: clean semantic models, governed metrics and the data engineering that feeds them. Unglamorous work. It’s also the reason everything above it works.
02/03
Activation SprintExploreDecisions, on tap.
- Executive dashboards
- KPI systems
- Self-service BI
- Governed templates
Once the foundation is in place, dashboards become trivial. This is where leadership stops chasing reports and starts using them. Think executive views and self-service BI that your team actually opens on a Monday morning.
03/03
AccelerationLet's talkAI applications, attached to your model.
- Copilot integration
- Fabric Data Agents
- Custom AI apps
- Forecasting
With a governed layer in place, AI becomes useful instead of risky. We build it together, honest about the frontier. Think Copilot integration, custom AI apps, forecasting and agents grounded in data they can’t misread.
Not sure which of the three you need? Take the twelve-question readiness check.
The shape of every project
Data in. Trust out. The middle is the whole job.
Layer 01
Raw sources
Layer 02 • we build this
Governed semantic layer
Layer 03
Trustworthy AI & BI
Selected engagements
Real foundations. Real outcomes.
A sample of client work, anonymised to respect confidentiality. Sectors and outcomes are real; identifying detail is not.
Hospitality & real estate
FoundationEnterprise BI, rebuilt on Fabric
A ten-month Microsoft Fabric and Databricks rollout replaced fragmented reporting with a governed platform. One CFO cockpit now consolidates every entity in the group, on shared definitions rather than reconciled spreadsheets.
- Microsoft Fabric
- Databricks
- Semantic model
Multi-brand retail
Foundation then AccelerationSemantic model as the AI on-ramp
We built a governed semantic model across several retail brands, then made it the foundation of an ongoing AI-enablement retainer. The textbook path from clean data to defensible AI.
- Semantic modelling
- AI enablement
- Retainer
Industrial manufacturing
FoundationGoverned BI across the plant network
Unified reporting for a manufacturer across its whole production network. Enterprise row-level security means every stakeholder sees exactly their own numbers, and only those.
- Row-level security
- Power BI
- Governance
Omnichannel e-commerce
Activation SprintLive finance analytics
Near-real-time financial reporting for an omnichannel retailer, built on Direct Lake and Eventstream. Finance leadership now sees performance as it happens. Not a day later.
- Direct Lake
- Eventstream
- Finance BI
How we work together
You leave the first call with a plan, not a pitch.
No blind retainers. The free consultation ends with a recommended path that is yours either way, and only the audit after it is billed. Then you decide what comes next: with us, with your own team, or not at all.
01 • Free
Roadmap
On the free consultation. A recommended path and a quote, and the document is yours to keep.
02 • 3 Days
Foundation Review
Fixed-price. We map sources, metrics and workflows, then write it all up.
03 • Scoped
Build
Foundation first, then up the tiers. Weekly check-ins. No black box.
04 • Your Call
Handover
We train your team and hand over, or stay on as a retainer. Your choice.
Small on purpose
Founder-led. Never a black box.
Ariavor is intentionally small. I lead every engagement myself, from the first call through to handover, so you are never explaining your business twice. The person who scoped the problem is the person who builds it, and the person you call when something breaks a year later.
/01
Foundation before features
/02
Defensible, always
/03
Written, not pitched
/04
Remote, close to the work
Published
Our most recent articles
Longer pieces from the build: what Fabric actually does under load, and the modelling decisions that decide whether AI can read your numbers.
Nothing published here yet
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Questions
The things people ask first.
What size companies do you work with?
Mostly SMEs with 20 to 500 people. They’re large enough to have real reporting complexity, yet small enough to need outside expertise rather than a full in-house BI team. Scaling startups outgrowing their spreadsheets are a natural fit too.
Do we have to commit to AI to work with you?
Not at all. Most engagements start at Foundation, and many happily stay there. AI becomes possible once the foundation exists. It’s never a prerequisite.
What does an engagement cost?
The first call costs nothing and carries no obligation. What follows is billed: a fixed-price audit, then build work scoped from that diagnosis, with a written breakdown before anything begins. No open-ended hourly surprises.
The stack we build on
- Microsoft Fabric
- Power BI
- Azure OpenAI
- Databricks
- Snowflake
- Direct Lake
Free consultation
Know Where Your Data Stands In 30 Minutes.
A free 30-minute consultation. No pitch, no invoice. You’ll leave knowing whether your data is ready for AI, and whether we’re a good fit.
Book Your Free Consultation(opens in a new tab)Let’s talk
Drop Us A Line.
Not ready for a call? Send over the shape of the problem, a rough timeline or a question about tooling, and you’ll get a considered answer from the person who would do the work.
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