What we build
Four kinds of AI workthat earn their keep.
We use AI where it removes real work from real people: reading documents, answering questions from company data and moving information between systems.
AI agents
Agents that carry out multi-step tasks across your systems — look something up, prepare a draft, update a record — and hand over to a person when a decision is needed.
Copilots on company data
Assistants that answer questions from your own documents, manuals and business data, with a link to the source behind every answer.
Document extraction
Invoices, delivery notes, orders and forms turned into structured data that lands directly in your ERP or accounting system.
Back-office automation
Repetitive workflows — sorting requests, matching documents, preparing reports — automated end to end and connected to the tools you already use.
Safety
Built to be trustedwith real data.
AI in a business process has to be predictable, auditable and easy to override. These rules apply to everything we ship.
- Human in the loop — people approve anything that sends, books or posts on their behalf.
- Data stays in the EU — EU hosting and EU-region model endpoints, chosen per project.
- Evaluation before go-live — every model is tested on your own documents and questions, not on demos.
- Full logging — every input, output and action is recorded, so results can be traced and reviewed.
- Least-privilege access — the AI only reaches the systems and records it actually needs.
- Manual fallback — when confidence is low, the task goes to a person instead of guessing.
Process
Small first step,measurable next ones.
We start with one workflow, prove it on your data and only then scale it up.
Pick one workflow
Together we choose a single, well-defined task where time is lost today and success is easy to check.
Prototype on real data
A working prototype runs on a sample of your documents or data, so you judge actual results instead of slides.
Evaluate
We measure accuracy against cases your team has already checked and agree on the bar for going live.
Integrate
The solution is connected to your ERP, shop or internal tools, with approvals and logging built in.
Monitor and improve
After launch we track quality, review edge cases and tune the system as your processes change.
Use cases
Where AI pays offfirst.
Two patterns we see again and again in companies that run on documents and data.
supplier-invoice.pdf
supplier
Delta Parts GmbH
number
DP-2026-1182
total
€3,412.80
✓ confidence 0.98
Supplier invoices into accounting
Incoming invoices are read, checked against orders and prepared for booking. Your team confirms instead of retyping.
Orders and delivery notes into ERP
Orders arriving by e-mail or PDF are converted into ERP documents, with unclear lines flagged for review.
Answers for sales and support
A copilot that finds product details, terms and past answers in seconds, so staff can reply faster and more consistently.
Internal knowledge in one place
Procedures, manuals and policies become searchable in plain language, with every answer pointing to its source.
Found 14 customers, worth €42.8k in last year's revenue. Top three:
- Northwind Ltd. — €9,120
- Blue Harbor d.o.o. — €6,480
- Alpine Supply GmbH — €5,930
Draft a win-back e-mail for all 14?
FAQ
Questions we hearbefore every AI project.
Do we need to train our own model?
Usually not. Most business use cases work well with existing models combined with your data, clear instructions and careful evaluation. We train or fine-tune only when testing shows it is worth it.
Where is our data processed?
We design for EU data residency by default: EU hosting, EU-region model endpoints and no use of your data for training third-party models. The exact setup is agreed per project.
Can it work with our ERP, shop or KigoCloud?
Yes. Integration is the core of what we do — AI is only useful once its results land in the systems your team already works in.
Will AI replace our staff?
That is not the goal. We automate the repetitive part of a job and keep people in charge of decisions, exceptions and anything customer-facing.
How do we know it works?
Before go-live we test on your own examples and agree on the quality bar. After go-live, logging and regular reviews show how the system performs.
What does it cost?
It depends on the workflow, data and integrations involved. Contact us and we will propose a scoped first step.