Make your own documents, data and knowledge usable for AI
A language model doesn't know your organisation by itself. If AI has to work with your own documents, product data or internal knowledge, that information has to be made available at the right moment and with the right permissions.
Does this sound familiar?
This question arises when general AI works well, but business-specific context is missing.
Knowledge is spread across many sources
Documents, databases and other systems each hold part of the context.
Copying into a prompt doesn't scale
Adding information by hand works for a demo, but not for structural use.
Information changes regularly
A static dataset quickly becomes outdated.
Not all knowledge is for everyone
Access rules from existing systems have to be preserved.
Where do you want to be?
You want to give AI access to relevant information of your own without putting everything into one uncontrollable data bin.
Relevant information at the right moment
The AI only gets the context needed for the current task.
Sources stay traceable
Important output can be traced back to the underlying information.
Permissions and freshness stay intact
Users only see what they are allowed to see, and changes in sources can carry through into the solution.
Why does this happen?
"Giving our own data to AI" sounds like one technical step, but usually consists of selection, retrieval, permissions and quality control.
See how we approach thisMore context is not automatically better
A model actually gives worse answers when too much irrelevant information is included.
Sources have different structures
A PDF, a relational database and a ticketing system each call for a different approach.
Data permissions don't disappear with AI
Retrieval has to respect the same access that applies elsewhere in the organisation.
Build & Integrate
With Build & Integrate we build the technical layer that gives AI targeted access to your data and knowledge. If feasibility or answer quality is still uncertain, an AI Prototype Sprint can first validate the most important sources and use case.
View this offerFixed price after scoping
Fixed price after joint scoping
- Result
- Working, integrated software your team can take over
- Duration
- Set in the scope
- Next step
- Handover to your team, or further development together
Why 9to5 for this?
The quality of an AI solution is often determined more by the context you provide than by the newest model. That's why we treat retrieval and data integration as fully-fledged engineering.
View casesSource and use case belong together
We don't just index everything because we can.
Existing permissions stay in charge
AI must not become a way around the access model.
No unnecessary platform layer
We only choose technical components the real problem requires.
What else fits your situation?
AI Prototype Sprint · €6,950 excl. VAT
From one concrete AI idea to a working end-to-end prototype that lets you actually test the key technical assumptions.
View offerHave an internal AI assistant developed
You want to give employees faster access to internal knowledge, documents and systems through an assistant that fits your organisation.
View use caseAdd AI to existing software, an app or SaaS
The product already exists. Now you want to add AI functionality without losing sight of the existing architecture, user experience and reliability.
View use case