// PRODUCTION-READY AI · SINCE 2019
Artificial intelligence. Thought through to the end.
We build AI architectures that run in your reality. Not in the lab, but in core operations. In weeks. So your systems do the work.
DEVELOPING PRODUCTION-READY AI SOLUTIONS FOR
01 // STARTING POINT
Here is what is happening in your company right now.
Retail & Commerce
Fragmented truths across your system landscape.
The ERP says A, the shop shows B. The same products sit in PIM, shop, and ERP at different states. Manual reconciliation costs margin and slows every attempt to scale.
Processes & Documents
Your data
is stuck in
unstructured silos.
Thousands of receipts, invoices, and cases a month, buried in PDFs and emails. Your team retypes what could long since be captured automatically.
Legacy IT
Your business-critical systems grew over time, they were not planned.
SAP, an AS/400, in-house developments from two decades. Stable and indispensable, but without native interfaces for modern, data-driven workflows.
02 // ARCHITECTURE
We integrate.
We do not replace.
Others advise a system change: months of migration, ongoing cost, an uncertain outcome. We bring the intelligence into what already runs at your company.
SAP stays SAP, Dynamics stays Dynamics. And they talk to each other.
Understand first, then solve
Technology follows the bottleneck, not the product catalog. We understand your business before we propose an architecture.
Deep integration instead of replacement
The AI sits on top of your existing systems through defined interfaces. No replacement, no interference with live operations.
Independence from day one
We build architectures that grow with the market and keep running without us. No dependency, neither on proprietary systems nor on individual people.
03 // SOLUTIONS
Three fields, one principle.
Every solution starts where your biggest lever is.
Retail & Commerce
problem
Product data that drifts apart between systems.
solution
Product Data Enrichment
Outcome
Ten thousand items on one consistent state, in two weeks.
Processes & Documents
problem
Receipts and cases that move through the department by hand.
solution
Document and Process Automation
Outcome
Captured, validated, and posted, without manual entry.
04 // REFERENCES
Proof, not promises.
Over 100 projects · 120,000 hours saved · 27 countries
BAUHAUS
“Xanevo gave us a self-service process that makes our Swiss teams independent.”
E-Commerce / Localization, BAUHAUS Switzerland
10×
faster processing
PUMA
6×
faster catalog delivery
Starting Point:
Global product catalog with over 12,000 items, updated seasonally across 40 markets.
Lösung:
Automated data harmonization. The catalog cycle dropped from weeks to days.
H&M
45%
lower cost
Starting Point:
High content volumes for over 8,000 new products per season.
Lösung:
AI-supported product data structuring. 2.5 full-time roles freed for strategic work.
Debo Digital
“Automation was the game changer for us: We can now deliver content and content briefs at a pace that was previously unthinkable.”
Managing Director, Debo Digital GmbH
n8n
workflow orchestrator
05 // APPROACH
First results in weeks,
not years.
1
Diagnosis
We examine your system landscape and prioritize the most critical bottlenecks.
Outcome
A roadmap and a solid business case.
2
Pilot
We bring a real use case with your real data into live operation.
Outcome
A running solution, not a presentation.
3
Scale
Only once the pilot convinces do we roll the architecture out across further areas.
Outcome
Productive operations and a team that runs it independently.
06 // STATUS QUO
The technology is ready.
Your infrastructure often is not.
The problem:
Most companies do not fail at access to modern AI models. They fail at missing interfaces, at unstructured data silos, and at the gap between lab conditions and live operations.
The consequence:
Pilots stay pilots, tools get licensed but not activated. The investment runs. The system stands. It does not get used.
07 // FREQUENTLY ASKED
Three questions that come up almost every time.
It depends on scope. You start with a clearly bounded budget and decide after the first result whether to scale. That way you have clarity before you invest.
The first use case runs in weeks. You see results before you decide on scaling.
Yes. SAP, Dynamics, IBM i, and grown in-house developments are exactly our field. We sit on top through interfaces instead of migrating.
08 // ASSESSMENT
Where does your company stand with AI?
Eighteen questions, five dimensions, an honest assessment. In a few minutes you know where you stand today and where the biggest potential lies.
09 // NEXT STEP
The first step is the easiest.
The question is not whether, but when. In 30 minutes you know where to start.
30 minutes
No sales pitch
A concrete recommendation