AI that performs in production

AI that survives production and the auditor.

I help companies build, advise on and lead AI that performs in production, not just in the demo. Twelve years building it, six of them inside regulated finance, where the bar is highest.

Stefan Ojanen
90%+
AML/KYC & credit decisioning automated at Danske Bank, across three countries
~1M CHF
Annual value from enterprise AI at Ringier, and 20,000+ hours given back
45x
ARR growth as Head of Product at Genesis Cloud, $100K to $4.5M

Built and shipped inside

  • Danske Bank
  • Ringier
  • Genesis Cloud
  • Scorable

Most enterprise AI dies after the demo.

MIT put a number on it: 95% of enterprise GenAI pilots show no measurable P&L impact. The demo is the easy 10%; integration, model risk and audit are the invisible 90%, and clearing it is what I have done for twelve years.

Size it for one of your own processes

01 Proof

Shipped, measured, in production.

Real systems inside real organisations, with the numbers attached. Each case opens into the full story.

90%+

AML/KYC & credit decisioning automated

Danske Bank · Enterprise · Nordic retail & SME banking

Manual onboarding replaced end to end across Finland, Sweden and Denmark, through a bank's second line of defence.

Read the full case · Skim in 60 seconds

Defined and delivered AML/KYC and credit-decision automation across retail and SME segments in Finland, Sweden and Denmark, replacing manual onboarding end to end. Pioneered the compliance-first delivery model the bank adopted organisation-wide. An earlier credit-automation design took SME automation from 5% to 50% and added ~€1M in annual profit.

Problem
Customer onboarding and credit decisions were manual across three countries, capping growth and costing the business unit in full-time staff.
Constraint
A systemically important bank: every change had to clear AML regulation, model risk, audit and a second line of defence before it could ship.
Approach
Designed the credit-automation architecture and defined the product vision for AML/KYC and credit decisioning. Built compliance in as a design input rather than an approval gate, and made the data infrastructure GDPR-ready before the regulation was in force.
Outcome
90%+ automation across retail and SME in Finland, Sweden and Denmark. SME automation went 5% to 50%, adding directly at least €1M annually. The compliance-first model was adopted bank-wide and cut compliance iterations at the approval stage.
Governance
Responsible for the product approval process covering every compliance aspect of the end-to-end financing products. The credit and AML/KYC onboarding automation sat inside that scope.
  • Banking
  • AML/KYC
  • Credit
  • Compliance-first

~1M CHF

Annual value from enterprise AI

Ringier · Enterprise · Media, 100+ publications

20,000+ editorial hours a year given back, and a RAG assistant serving 2M+ monthly users.

Read the full case · Skim in 60 seconds

Led enterprise AI transformation recovering 20,000+ editorial hours a year, including the team working on AI Forge, the group's AI toolbox. Shipped a RAG assistant that lifted session duration 39% for 2M+ monthly users, across 380K+ AI-assisted content events a year.

Problem
Editorial work across more than a hundred publications was manual and repetitive, consuming hours that should have gone into journalism.
Constraint
Public-facing output for a major publisher: anything generative carried reputation and editorial-trust risk, on top of the usual production constraints.
Approach
Ran the AI transformation end to end. Led the team working on AI Forge across five content use cases, and shipped a RAG assistant for Blick.ch plus an agent that joins meetings and maintains JIRA tickets. Redesigned the MLOps setup on SageMaker underneath it.
Outcome
About 1M CHF of annual value and 20,000+ hours recovered, roughly twelve full-time staff. 380K+ AI-assisted content events a year. The RAG assistant lifted session duration 39% and pageviews per session 35% for 2M+ monthly users.
Governance
Reputation and content risk on a publicly exposed RAG system managed directly, with editorial guardrails around every generative surface.
AI Forge featured at Ringier's SPEAK 2026
  • Enterprise AI
  • RAG
  • Agents
  • MLOps

Acquired

Drove product-market fit to a successful exit

Scorable · Start-up · Explainable AI for asset managers

Explainable AI for fixed income, taken from inherited MVP to product-market fit and acquisition by BondIT.

Read the full case · Skim in 60 seconds

Took an inherited MVP for explainable AI in fixed-income asset management to product-market fit, directly enabling acquisition by BondIT. Explainability treated as a first-class, regulator-ready feature, not an afterthought.

  • Explainable AI
  • Asset management
  • Fixed income

$100K → $4.5M+

ARR as Head of Product

Genesis Cloud · Scale-up · AI cloud infrastructure

Built the GPU-compute offering and the partnerships that scaled Germany's first AI cloud 45x.

Read the full case · Skim in 60 seconds

Owned the product vision and roadmap that scaled ARR 45x. Built the GPU-compute and MLOps offering, forged partnerships with Intel Habana and NVIDIA, and landed the largest enterprise contract at the time (€300K+).

  • AI infrastructure
  • GPU compute
  • Enterprise contracts
Stefan is one of the brightest guys I've worked with. He went often beyond his role as product manager to also get his hands dirty in operations and architecture, and took on communicating complex and sometimes difficult messages to executives, and orchestrating complex operations, often dealing with compliance, with stakeholders across multiple organizations.
Hayk Yegoryan, Partner, McKinsey & Company
Stefan is an expert in Artificial Intelligence and High-Performance Computing, and a remarkable professional. His expertise spanned both software and hardware, going way beyond the level of depth I would typically expect from a Product Manager. He was always reliable, consistently meeting our milestones, and I genuinely enjoyed working with Stefan and his team.
Dan Alistarh, Professor, MIT & ISTA

02 Teams & culture

The capability has to outlast me.

The people and the longer story
Ringier team offsite, Slovakia
Ringier team offsite, Slovakia
First Berlin Builder Circle, Rasa office
First Berlin Builder Circle, Rasa office
GDG Cloud Berlin x MLOps Community, Google Berlin
GDG Cloud Berlin x MLOps Community, Google Berlin
Genesis Cloud Portugal Retreat
Genesis Cloud Portugal Retreat

03 EU AI Act & ISO 42001

The deadline moved. The work did not.

High-risk obligations moved to December 2027. The Article 50 transparency duties went live in August 2026 regardless, and the firms that wait will retrofit a portfolio instead of building to the standard. I get you certification-ready.

The timeline and the standards, in full

Get started

Find your highest-ROI AI automation, safely.

Tell me about the manual process that is costing you the most. If an Audit is a fit, I will come back within two business days with how it would work. If it is not, I will tell you that too.

Questions about data, compliance or fees? The FAQ answers them

Start with a call

Thirty minutes, no pitch. If an Audit is not the right next step I will say so.

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Prefer to write?

Length
Two to three weeks
Fee
Fixed, agreed before we start
You get
Automation opportunities ranked by ROI and risk
Plus
Compliance constraints mapped per use case
Outcome
A business case you can take to the board

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