Services - AI implementation
Everyone is experimenting with AI. Little of it reaches production.
We develop the implementations that do - securely connected to your business data.
Public AI models know nothing about your organisation. We build the secure bridge between powerful language models and your internal data, so you get assistants that understand your business - without sensitive data ending up in someone else’s model.
- Internal chatbots and assistants on your own knowledge and data
- Document processing and automation of manual steps
- Decision support with verifiable answers
- A prioritised, realistic AI roadmap via the QuickScan
Open about our stack
Model-independent: Claude · GPT · open source - on your own infrastructure or in the EU cloud
Start here - AI QuickScan
Know in one session where AI helps your organisation - and where it doesn’t.
A focused scan of your processes. You leave with a prioritised, realistic AI roadmap - no buzzwords.
1 session
with senior engineers
5+ use cases
scored on value & effort
1 roadmap
ready to execute
The trade-off
Where AI does and doesn’t work in an organisation
The work first, then the technology - we start on your work floor.
AI works where the work repeats and the outcome can be checked. That is exactly where most organisations lose the most manual hours - and where the gains are. AI does not work with vague goals, missing or messy data, or decisions where a single mistake causes real damage without anyone checking.
We make that distinction up front, not after something has been built.
Where AI proves itself
- Reading and structuring documents
- Moving data between systems
- Answering questions based on your own knowledge
That is why every engagement starts with the AI QuickScan: one session in which we scan your processes and score the use cases on value and effort. The most promising one becomes a pilot on your own data, with quality criteria agreed in advance. So you know within weeks - not months - whether AI can carry the work. If the pilot doesn’t meet the criteria, we scale back or stop; that’s possible because every step is small and budget-controlled.
What we build falls into two tracks. If the manual work sits in document flows - invoices, contracts, case files - then AI integration & document processing explains how we build language models directly into your workflow. If work needs to be carried out autonomously, within boundaries you define, AI assistants & agents is your route. Both rest on the same foundations: secure access to your data, measurable quality and a human in the loop where it matters.
What we do
One starting point, two tracks.
Every route starts with the AI QuickScan. From there we develop along two tracks - on the same foundations: secure access to your data, measurable quality and a human in the loop where it matters.
AI QuickScan
The starting point: one session on your work floor, and you leave with a prioritised, realistic AI roadmap.
AI integration & document processing
AI safely inside your existing processes: document flows, automation of manual steps and decision support with verifiable answers.
AI assistants & agents
Assistants and agents on your own knowledge and data, carrying out tasks autonomously - within boundaries you define.
Rather get straight to it? Jasper Kums, partner at eenvoud, is happy to think along with you about where AI does and doesn’t work in your organisation - no strings attached.
In practice
AI automationOwn product - Eenvoud × Helder bij Letselschade
Calculations that used to be specialist work in scattered documents are now transparent, uniform and reproducible per case file - available on the market as a product.
From idea to production
A working pilot in weeks.
No months of upfront planning: every phase delivers something you can steer on.
1 session
QuickScan
We scan your processes and score the opportunities on value and effort. You leave with a roadmap.
week 1-4
Pilot on real data
The most promising use case becomes a working pilot on your data - with measurable quality criteria, before anything goes live.
ongoing
Into production
What works goes live in a controlled way, connected to your systems. The same team monitors and keeps improving.
What we learned
Beyond the demo.
An AI demo is built in an afternoon. These three lessons make the difference between a demo and something that carries the work.
The gains are in the boring steps
Not the spectacular chatbot - document processing and repetitive manual work deliver the fastest return, like the receipt recognition in Letselinzicht.
No production without evaluation
Before going live, we define measurably when an AI answer is good enough. What you don’t measure, you can’t trust.
Your data is the real work
The biggest part of an AI implementation is making your data accessible, clean and secure. Skip that and you’re building a demo.
Frequently asked questions
What you want to know before you start.
Where do we start with AI in our organisation?
Not with the technology, but with the work. That is what the AI QuickScan is for: in one session we scan your processes, score five or more use cases on value and effort, and you leave with a prioritised roadmap. You start with the question that pays off most right now - not with whichever model happens to be in the news.
What does AI implementation cost?
That depends on the use case, your data and your systems, so we won’t name a figure before we know them. We work scope-first: the QuickScan has a fixed, short duration, and after that we develop in small, budget-controlled steps - after each step, you decide what happens next. You get a concrete estimate after the first conversation.
Do we need our own AI expertise to get started?
No. You know your processes, your customers and your data; we bring the model, integration and evaluation expertise. During the pilot your team learns to work with the results and judge them - that is all it takes. The technology underneath remains our job, also after go-live.
What if AI doesn’t deliver anything for us?
Then we say so. Sometimes the honest outcome of a QuickScan is that plain automation or a better workflow delivers more than AI - and you hear that in the same session. And if a pilot doesn’t meet the quality criteria we agreed in advance, we scale back or stop. Because the steps are small, you know within weeks and without a large written-off budget.
How does this work with the GDPR?
In broad strokes: your data remains yours. We work model-independently and run on your own infrastructure or in the EU cloud where needed, with processing agreements that fit the GDPR. Your data does not train anyone else’s models, and before every pilot we agree which data is processed where. How that works out per document flow is covered under AI integration & document processing.
Let’s talk
From experiment to production.
Curious where AI works for you - and where it doesn’t? We’re happy to think it through with you.