Friction
We choose one process where time, knowledge or quality is being lost.
AI & smart automation
AI that removes repetitive work, shows its sources and keeps people in control.
Talk about your project↗︎03AFriction03BSources03CPilot03DRollout
Not a fixed package. A clear role.
We start with repetitive work or knowledge that is hard to access. Then we design a solution with clear checks and human oversight, from document processing and an internal knowledge assistant to a predictive model or bespoke workflow.
You will recognise this if:
- 01Your team retypes the same data from emails, PDFs or forms into another system.
- 02Knowledge lives in people's heads or in folders nobody can find.
- 03The same questions from customers or colleagues come back every week.
- 04You want to do something with AI, but without sensitive data simply leaving the building.
Not AI for its own sake. Less routine work, with clear checks in place.
Sources
We agree on the data, permissions and human oversight before building.
Pilot
A working prototype proves its value with real examples.
Rollout
Monitoring and feedback keep the solution reliable and useful.
What we can deliver.
- 01
AI opportunity assessment
Together we find the processes where AI demonstrably saves time or errors, and we also say where it makes no sense.
- 02
Knowledge bases and semantic search
Search your own documents by meaning, with answers that point to their source.
- 03
Document processing
Data from invoices, forms or emails read automatically and prepared for review.
- 04
Assistants and chat interfaces
An assistant for your team or customers that answers within agreed limits and refers on when it does not know.
- 05
Workflow automation
Recurring steps between systems run automatically, while a person handles the exceptions.
- 06
Monitoring and human oversight
Insight into what the solution does, with checkpoints and logs, so you can keep trusting it.
Your input
- A concrete process or question that currently eats up time.
- Real examples: documents, questions or data we can test with.
- Someone who knows how the work is done today and can judge the result.
- Clarity on which data may be used and where it has to stay.
What sets the planning
- How many sources and systems are connected
- How sensitive the data is and which requirements apply to storage and access
- A prototype, or a solution a team uses every day
- How much review and monitoring is needed
After a short introductory call you receive a proposal with fixed parts, planning and investment. No vague provisional items.
Request a proposal↗︎This is how the service becomes real work.
What people often ask.
Ask your own question↗︎01Is it safe to use our company data with AI?+
We agree on that up front: which data may be used, where it is processed and who has access. Where needed we choose processing within the EU, and a person keeps the final check.
02What if the AI gives a wrong answer?+
That is why we design with sources and review. Answers point to the document they come from, doubtful cases go to a person and we keep track of what the solution does.
03Do we have to start a big AI project straight away?+
No. We start with one process and use a working prototype on real examples to show whether it adds value. Only then do you decide whether we build further.
04How much does an AI solution cost?+
That depends on the process, the data and how widely the solution is used. After a short exploration you receive a proposal with fixed parts, planning and investment, without vague provisional items.