From AI pilots to systems your business runs on.
We work with your teams to identify the workflows worth improving, build the right software around them, and run it with you.
The gap
Everyone bought AI. Almost nobody’s P&L noticed.
88% of AI agent pilots never reach production. Not because the models aren’t good enough - the failures trace to governance, data readiness and observability, and roughly 70% come down to people and process, not algorithms.
Buying seats is not adoption.
The seats were the easy part: 88% of companies report using AI somewhere; about 39% say it has moved the P&L. Every company this size has AI subscriptions - very few have changed a single workflow with one.
What separates the ones that survive
- Named ownership
One person answerable for the system in production. Not a licence, not a committee.
- A metric agreed before the build
Success defined as a business number before anything gets built - not argued about after.
- An executive sponsor
Budget and a six-month commitment behind the system - not a pilot orphaned at the first re-org.
- Automated evals
Continuous, automated tests of what the system actually does. The two bars here are that difference.
With a metric agreed upfront, about 54% succeed; with an executive sponsor, about 68% against 11% without.
Figures: IDC, Deloitte, Forrester, Gartner, 2026.
What we build
Not another subscription. Systems in your name.
Five shapes the work usually takes. Everything lands on your infrastructure, in your name - built to be owned, not licensed back to you.
The replacement for the subscription nobody fully uses.
The €50–80k-a-year platform your team works around in spreadsheets, rebuilt as one tool that fits the actual workflow. It never renews, because you own it.
Renewal signals your CRM doesn’t see.
Health scores that reflect value delivered, not logins. QBRs and reports that assemble themselves. Onboarding handoffs that don’t drop the customer between teams.
Agents that survive contact with production.
Scoped to one workflow and measured from day one. An agent is software with a failure rate - evals mean you know that rate before your customers do.
One reconciled view across systems that don’t talk.
ERP, CRM, support desk, accounting - agreeing on the same customer and the same numbers. Once, correctly.
The workflow that only works because someone remembers it.
Approvals, handoffs, escalations, month-end reporting - automated end to end, every step visible, nothing living in one person’s head.
The engagement
Four steps from diagnosis to a running system.
A fixed-price build against a metric agreed upfront, then ongoing ownership - priced like the hire you don’t make, not like another tool.
- 01
Diagnose
Find the workflow worth automating, and agree the business metric that defines success before anything gets built. Some problems stop here - that’s the point.
- 02
Scope
Fixed price, fixed outcome, and a named executive sponsor with budget and a six-month commitment. The strongest single predictor of success there is.
- 03
Build
8–12 weeks, on your infrastructure, in your name, with evals running from day one. At handover it works and it’s yours - nothing held back.
- 04
Run
Monitoring, changes, updates, the 3am accountability. The part that decides whether the system is still alive in a year - and the part we don’t hand off.
The economics
€80k a year, forever - or a build you own.
A subscription charges every year, forever, and bends your workflow to fit it. A build costs more up front, less every year after - and it’s yours. Where the lines cross depends on your numbers; that math happens in the first conversation, in the open.
Who runs it afterwards
Generating software got cheap. Owning it did not.
Writing the code was never the expensive part. This is, and it doesn’t stop when the build does:
A build that ends at handover leaves you an artifact and a folder of credentials. What you get here is an operated system, with someone answering for it by name.
Anyone can generate the code now. Almost nobody wants to answer for it at 3am.
Why us
You’re not paying to teach us your business.
What you’re buying is judgment: which workflow to pick, which number defines success, where automation breaks the way work actually happens. It comes from fourteen years running customer success, renewals and revenue operations - not observing them.
A dev shop needs six weeks of discovery to learn what a QBR is.
Here, that discovery is already done. The diagnosis starts at your numbers, the build starts in week one - and the business case arrives in the language your CFO reads.
Behind it: founding-team customer success at Careem, through the Uber acquisition · enterprise CS and usage-based pricing at Trusted Shops · Head of CS with a €20M+ portfolio at a DACH platform.
You already know which workflow it is.
A first conversation costs nothing. You bring the workflow; you leave with a view on whether it’s worth building, the number that would prove it - and a straight no if it isn’t.
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