AI inside your systems. Engineered, not advised.
Big consultancies sell you a roadmap. We sell you a working system. We integrate LLMs into the software your company already runs, with EU-compliant architecture and costs you can predict, because we run the same AI infrastructure for our own products every day.
Where AI actually pays off in a company that already works
You have probably already heard the other pitch. A large consultancy runs a discovery, produces a maturity assessment and a roadmap, and leaves. The roadmap is not wrong. It is just not software, and nothing in your company works differently on Monday morning.
The valuable work in a mid-market company is narrower and far more concrete. Documents that arrive as PDFs and get retyped into an ERP. Customer emails that somebody triages by hand for three hours a day. Knowledge sitting in a shared drive nobody can search. Quotes assembled by copy and paste. These are the workflows where a well-engineered AI layer removes real hours, and they are almost never the ones on the slide.
So we start from your systems as they are: the CRM you are not going to replace, the ERP with fifteen years of history in it, the mailbox everything flows through. We put the AI layer beside them, on EU infrastructure, with an audit trail and a cost ceiling. Then we prove it on one workflow before anybody signs up for a rollout.
A pilot that pays for itself, or an honest answer that it will not.
The parts that make the difference.
We write the code
The people on the call are the people in the repository. No handoff to a delivery team you never met, no offshore subcontractor, no account manager relaying your questions to someone else.
Real cost models
API spend, hosting, and maintenance modeled before you commit and metered after, with caps in the code. Nobody gets a surprise invoice because a loop ran overnight.
EU and GDPR by architecture
Data residency, model choice, retention, and audit trail designed in at the start rather than patched on for the auditor. Sensitive processing can stay inside the EU, or on your own servers where the law requires it.
It connects to what you already run
Sales, operations, and finance systems, mailboxes, file shares, databases. We integrate through the interfaces your vendors actually expose, and we tell you plainly when a system has none.
Measured, not assumed
Every pilot ships with the number it has to move: hours saved, response time, error rate, cost per document. If the number does not move, we say so and you stop.
Proven in our own production
Document processing, customer triage, internal knowledge, agent workflows. Our own operations run on AI assistants every day, so every pattern we propose has already survived our own use of it.
A written process, with dates attached to it.
Four stages, each with a decision gate at the end. The pilot is deliberately small and fixed-price, because the point of it is to find out cheaply whether the rest is worth doing.
Systems audit
We map how work and data actually move through your company, then rank the candidates by value rather than by novelty.
- Map of your systems and where data really flows
- Ranked list of candidate workflows
- Cost and savings model per candidate
- The honest list of where AI does not fit
Pilot
One workflow, end to end, on your real data. Small enough to fund out of a department budget, real enough to prove the case.
- One workflow live on your real data
- The target metric measured before and after
- EU-hosted, audit-logged, cost-capped
- A go or no-go you can defend internally
Rollout
Extend what the pilot proved across the processes next to it, and drop what it disproved.
- The proven pattern extended across processes
- Integrations into the systems of record
- Your team trained on the new flow
- Everything the pilot disproved, dropped
Operate
Models change every few months. We keep quality, cost, and uptime where they were on the day you signed off.
- Monitoring and output quality checks
- Cost tracking per workflow
- Model upgrades as providers move
- New automations as they prove out
You can stop after any stage and keep everything built up to that point, in your own accounts.
What you actually get.
Not a category list. The concrete things that exist at the end, and that stay yours.
Integration
- Connectors into your CRM, ERP, mailbox, and file storage
- Document ingestion: PDFs, scans, spreadsheets, attachments
- Retrieval over internal knowledge, with permissions respected
- Write-back into the systems of record, not just a separate dashboard
- Scheduled and event-driven runs, not manual copy and paste
AI engineering
- Model selection and routing across EU-available providers
- Evaluation sets, so quality is a number and not an opinion
- Human review in the loop where the stakes require it
- Guardrails, fallbacks, and hard spend caps
- Open models on your own infrastructure when data cannot leave
Compliance and operations
- Data residency and retention decisions, documented
- Full audit trail of what the system saw and did
- Access control aligned to your existing roles
- Monitoring, alerting, and a named person to call
- Data processing agreement and vendor documentation
What we don't do.
Saying it out loud saves everyone a call.
Prices published, before you ask.
Every project is quoted on its real scope; these ranges show the order of magnitude so you know where you stand before the first call.
One workflow automated end to end on your real data, with a measurable result. If it doesn't pay for itself, you'll know fast.
AI across your core processes: documents, customer communication, internal knowledge. Your team trained, costs under control.
We keep it running and improving: monitoring, cost tracking, model upgrades, and new automations as they prove themselves.
Questions we get asked.
Do we have to move our data to the US?
No. We select providers with EU data residency, and for the most sensitive workloads we run open models on European infrastructure or on your own servers. That choice is made explicitly during the audit, with the trade-offs written down.
How much does the AI itself cost to run?
For most mid-market workflows, tens to a few hundred euros a month in API spend, far below the labor it replaces. We model it per document or per request before you commit, and meter it live afterwards.
What if the pilot fails?
Then you paid a small fixed price to find that out in five weeks instead of committing to a rollout. That is what the stage is for. We have told clients to stop before.
Our IT team is small. What do they have to do?
Give us access and answer questions about the systems. We do the engineering. At rollout we train the people who will use it and document what your team needs in order to support it.
Will this replace people?
In our experience it removes the part of the job nobody wanted: retyping, sorting, searching. We design for a person reviewing the output wherever the stakes are real, and we tell you plainly when a workflow is genuinely fully automatable.
Can you work with our existing software vendor?
Yes, and often we have to. We are used to integrating around a vendor's API limits, and to being the ones who read their documentation properly.
Selected projects from this service portfolio.
A selection, not the full list. Part of our client work sits under NDA and is not shown here.
AI product development
From idea to finished product. We design, build, and run digital products the same way we build our own: first version live in weeks, built to last.
Custom platforms
Portals, management systems, internal tools, marketplaces. Solid platforms delivered in weeks and looked after once they're live.