OSIdbtCube
Compute
Do all tools calculate the same metric identically?A library of metric definitions on top of existing tables. Standardised as YAML.
d.APThe Knowledge Layer
AI understands data. But not your enterprise.
d.AP translates your organisation's knowledge - facts, relationships and rules - into a universal structure, immediately executable by any AI.
Modelled once, usable everywhere.
Why AI gets stuck in the enterprise
It's not just data that's distributed across the enterprise, the knowledge is too.
Your company's most valuable knowledge is not stored in databases but in the minds of your employees. It consists of years of experience, informal rules and complex interdependencies. To an AI, this implicit knowledge has so far been entirely invisible.
If AI is to do more than answer simple questions and instead act autonomously on your behalf, this scattered knowledge must be digitalised and logically connected. That is exactly the bridge d.AP builds.
d.AP · Knowledge Layer in Action)
Whatever the question, the answer will always be correct.
Aluna is d.AP's AI agent. Answers that are reliable — with full derivation, sources and explanation. No simple chat, no hallucinations.
Next step
Experience Aluna — live, in a demo environment.
Use cases
What you can do with d.AP.
Examples of how companies optimise their operational processes with connected knowledge that AI can use.
01Scroll →
01 — Supply Chain
Supply Chain Risk
See instantly which suppliers, parts and routes are affected — before downtime starts costing you.
Learn more →02 — QualityProduct & quality analytics
Engineering, production and after-sales in a single view. Find root causes of defects faster.
Learn more →03 — ControllingControlling & Steering
Real-time transparency across budgets and forecasts — grounded, reliable.
Learn more →04 — RevenueUpselling & Cross-Sell
Connect CRM, contracts and support — revenue potential in seconds.
Learn more →05 — EAMEnterprise Architecture
Systems, processes and costs in one view — smarter IT, less risk.
Learn more →06 — OperationsProduction & Operations
A live view of orders, utilisation, defects. Agents right on the layer.
Learn more →Your use case
Those were examples. Perhaps you are facing an entirely different challenge?
Architecture
Your systems stay. The knowledge becomes usable.
d.AP does not replace an operational system or a data lake. It lays a semantic layer over what you already have and makes enterprise knowledge accessible to every AI through a single endpoint.
What d.AP delivers
- Secure connection to every internal and external data source.
- Reliable usage Answers are based on your knowledge, not on statistical patterns.
- Full provenance Every answer is traceable to source, logic and filters.
- Immediately operational Enterprise-ready, incl. roles & permissions, SSO and scalability.
Next step
Let's have a conversation about your situation.
A semantic classification
Four things are called “semantic”. They don’t all mean the same thing.
- Semantic Layer
OSIdbtCube
Compute
Do all tools calculate the same metric identically?A library of metric definitions on top of existing tables. Standardised as YAML.
- Semantic Search (RAG)
Vector DBEmbeddings
Retrieve
Which documents sound most similar to my question?Text chunks ranked by statistical similarity. Excellent for finding passages — it retrieves, it does not know.
- Labeled Property Graph
Neo4jGQL
Connect
How is everything connected, so that I can traverse paths?Data as nodes and edges with properties. Optimised for traversing relationships at speed.
- RDF Knowledge Graph
RDFSHACLOWL
Understand
What do things mean — and which rules hold when machines act on them?A formal model of your business terms (the ontology), populated with your real entities (the graph). Meaning, rules and data in one place.
Vector DBEmbeddings
Retrieve
Which documents sound most similar to my question?Text chunks ranked by statistical similarity. Excellent for finding passages — it retrieves, it does not know.
Neo4jGQL
Connect
How is everything connected, so that I can traverse paths?Data as nodes and edges with properties. Optimised for traversing relationships at speed.
RDFSHACLOWL
Understand
What do things mean — and which rules hold when machines act on them?A formal model of your business terms (the ontology), populated with your real entities (the graph). Meaning, rules and data in one place.
We are proud to have supported these companies
… and many more
Core elements of d.AP
It is always about: making knowledge usable.
d.AP turns enterprise knowledge into a form AI can interpret and execute directly.
01 — Modelling
Ontology Workbench
OWL Modelling · RML MappingA visual editor for modelling your world and linking it to the real data. So that this does not remain the domain of data engineers.
Learn more02 — Referencing
Metrics Library
KPIs · Metrics · EvaluationsArbitrary metrics, KPIs and evaluations can be generated automatically, stored in a library, and referenced from any external system through the API.
Learn more03 — Analysing
Analysis Agent
GenAI · Aluna · Data analysisRun complex data analysis in natural language as a business team — and be certain that the answers you receive are correct.
Learn moreAn enterprise-wide knowledge layer built for the age of agentic AI.
Discover d.AP)
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Sovereignty
From Europe, for the whole world.
We build on European technology and open standards such as RDF out of conviction — without open technology there is no sovereignty.
Beyond that, our architecture is designed for the highest level of information security and European data protection.
Voices
The application delivers.
Voices
from deployments
of d.AP
from deployments
of d.AP
A selection
Finally, an AI that does not hallucinate, and I see the source right there with it.
Enterprise ArchitectManufacturing
Use case Knowledge Layer for Service & Support.
Go-live with seven sources.
The speed at which use cases were put into production is unique, and so is the ROI.
Head of Data & AIAutomotive
Use case Connecting five business domains into one integrated knowledge layer.
01Manufacturing
Finally, an AI that does not hallucinate, and I see the source right there with it.
Enterprise ArchitectManufacturing
Use case Knowledge Layer for Service & Support.
Go-live with seven sources.
02Automotive
The speed at which use cases were put into production is unique, and so is the ROI.
Head of Data & AIAutomotive
Use case Connecting five business domains into one integrated knowledge layer.
Next
Further insights
Dive deeper.
Common questions
What decision-makers ask first.
Security, integration, time-to-value.
Choose a topic — or read through them all.
Your question is not covered? We reply personally.
Let's talk
You don't have to start from zero. Talk to us.
Every new agent, every copilot starts from zero — unless they share a knowledge layer. In 30 minutes we talk through your challenges and demonstrate d.AP live.
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