Enterprise knowledge and vector search
Build retrieval-augmented generation (RAG) with company documents, business systems and HANA Cloud vector search. Return source references so people can review the information behind an answer.
BREDA, THE NETHERLANDS · ACROSS EUROPE
Private AI.
Your knowledge, connected.
Private AI engineering for businesses across Europe. Make company knowledge useful with access and deployment controls that fit your organization, from private cloud to on-premises or self-hosted models where appropriate.
Discuss private AIWhere we can help
Useful answers start
with the right access.
Company documents and business systems hold valuable context. We design knowledge assistants that connect people to relevant information while accounting for source permissions, deployment requirements and operational ownership.
Permission-aware retrieval
Design retrieval around the access a user has to company information. Identify source owners, permission boundaries and how changes in access need to reach the assistant.
Private deployment choices
Evaluate private cloud, on-premises and self-hosted model options against your requirements. The appropriate approach depends on your data, infrastructure, access needs and operating constraints.
Knowledge connected to action
Bring private knowledge into CAP applications and agents through defined APIs and MCP tools. Keep clear boundaries between retrieval, a proposed action and an update to a business system.
From context to operation
Map the knowledge.
Design the boundaries.
Expert consultancy or delivery with your team. The starting point is a specific business need and a clear first scope.
Understand the sources
Identify the documents, systems and users involved. Review who owns the information and what access rules the assistant needs to follow.
Choose the architecture
Agree on the deployment, retrieval and model approach. Define where information is processed and who operates each part of the system.
Evaluate before expanding
Test answers, source references and permission behavior against real use cases. Establish monitoring and maintenance before adding more sources or actions.
What your team receives
- A knowledge-source map, permission model and deployment decision.
- A working retrieval flow with source references and agreed evaluation cases.
- Guidance for source updates, access changes, monitoring and ownership.
One connected ecosystem.
Private knowledge can support an employee assistant, a custom application or an agent connected to SAP and business APIs. We connect these parts around a defined task, with review before actions where appropriate.
Before we start
A little more
context.
Can private AI run on premises or with a self-hosted model?
Those are deployment options we can evaluate alongside private cloud. The choice depends on the data, infrastructure, model capabilities and operational requirements of your organization.
How can a knowledge assistant respect existing permissions?
We design retrieval around user access to the underlying sources and test permission behavior against the agreed requirements. Source ownership and changes to access are part of the architecture discussion.
Does a private deployment automatically make an AI system compliant?
No. Deployment is one part of the design. Your data flows, source permissions, model behavior and operational responsibilities need to be assessed against your own requirements. We work with your team to define the technical boundaries.
Let’s connect
Let’s make
what’s next work.
Tell us about your private AI project,
your existing systems and what you want to achieve.