About paterhn

AI Development Studio

Engineers building production AI. Working systems on your infrastructure. Yours to own.

We ship AI that works. Multi-agent systems, custom LLMs, and production deployments.

First LLM-style agent shipped in 2019. Multi-system orchestration since 2018. Machine learning roots back to 2001. We were early to deep learning, early to transformers, early to agents.

Swiss HQ. Global delivery. Your IP.

External R&D

External R&D That Ships

Everyone's talking about AI. Few are shipping it. Internal teams are stretched. Governance adds friction. Pilots stay pilots. The models are ready, most organisations aren't.

We are your external AI R&D function, a senior engineering team that unblocks delivery when internal capacity is constrained, governance is complex, or initiatives are stuck between prototype and production.

We don't sell recommendations. We ship auditable AI in your environment, then transfer the capability to your organization.

NotConsultants who speculate
AreEngineers who build
NotVendors who lock in
ArePartners who hand over
NotContractors who disappear
AreTeams who transfer knowledge
NotAdvisors who deck
AreBuilders who ship
Our History

The Timeline

Two decades of building what works.

2001
ML roots take hold
Signal processing, prediction, optimization. Custom implementations before frameworks existed. Models in production, not just research.
2013
Deep learning goes mainstream
Early adoption of CNNs. GPU-accelerated training. Real deployments in signal processing and prediction systems.
2017
paterhn is founded
Copenhagen, Denmark. Physicists and engineers building production AI. Manufacturing, IoT, field devices, predictive maintenance. Tangible AI that made a difference on a daily basis.
2018
Closed-loop orchestration
Multiple models coordinating and self-correcting in production environments. RNNs and NLP pipelines in production.
2019
GPT-2 era agents in production
Transformer-based systems with retrieval and tool use. Early end-to-end decision loops orchestrating language models at scale.
2020
Custom domain models
Client-owned language models trained on private data. Beating commercial benchmarks. Full IP ownership.
Today
Swiss HQ (Zug/Zürich)
Multi-agent systems orchestraed at enterprise scale, across industries, global delivery. Two decades of ML, now in production worldwide. Builders of end-to-end decision loops that close the gap between model and operation.

About paterhn

Uncertainty isn't the enemy. It's the signal.

Most of us are computer scientists, engineers, and physicists. We've spent careers working with probabilistic systems, stochastic processes, and quantum mechanics. We don't pretend the world is deterministic. We know it isn't.

Data is inherently noisy. Reality is inherently random. Most approaches try to eliminate uncertainty, smooth it out, average it away, pretend it doesn't exist. We work with it.

The best AI systems don't fight randomness. They learn its structure. They quantify what they don't know. They make decisions that account for uncertainty rather than ignore it.

That's what "pattern" means to us: not false precision, but honest signal extracted from genuine noise. Decisions that acknowledge what we know, what we don't, and what we can learn.

100+ computer scientists, engineers, and physicists. Frederik Bonde started building ML systems in 2001 and founded paterhn in 2017. The team has grown. The approach hasn't changed.

First principles, not frameworks.

We don't import someone else's methodology and call it strategy. We look at the problem, the data, the constraints, and reason from there.

Every engagement starts with a question: what would working software look like in 12 weeks? Not a roadmap. Not a deck. Software you can run, measure, and improve.

Think big, start small. Prove value fast. Scale what works.

We've shipped production AI since 2001. We know what breaks. We build systems that don't.

When bees build hives, they don't plan hexagons, they build circles. The hexagonal structure emerges from pressure, individual cells pushing against neighbors until the geometry optimizes itself. No central architect. No master plan. Just local rules creating global order.

This is what multi-agent orchestration looks like.

Our mark is nested hexagons, each layer slightly rotated from the next. Not perfectly aligned. Intentionally offset.

Because perfect alignment is a fiction. Real systems have drift. Real coordination requires tolerance for variation. The rotation acknowledges what we know to be true: structure emerges not despite imperfection, but through it.

The orange core is the signal, concentrated, unmistakable. The outer rings are context: supporting structure that recedes so the signal can speak.

Simple form. Considered execution. Like the work itself.

You'll notice the A in "AI Development Studio" isn't a standard A. It's Λ, the Greek letter Lambda.

This isn't a gimmick. It's philosophical alignment made visual in a single glyph:

To physicists it's a fundamental constant. To probabilistic modelers it's a rate. To functional programmers it's the pure function. For us it's the quiet force that turns uncertainty into better decisions.

We named the company after pattern recognition in noise, and Λ is the mathematical symbol for the hidden parameters that generate those patterns.

It feels inevitable once you see it.

No acronym. No hidden meaning. Just a belief that uncertainty, properly understood, is a force for better decisions, not worse ones.

ΛPhysics, quantum mechanics, eigenvalues - the fundamental constants
ΛDecay rates, stochastic processes - embracing uncertainty
ΛFunctional programming - clean, composable systems
ΛCosmological constant - the quiet force that shapes everything
Philosophy

Our Philosophy

Strategy is hypothesis. Shipping is proof.

Start from first principles. Go to working prototype. Scale what works. Ditch what doesn't.
In shipping, we discover. Only by moving from PowerPoints to production do we find what actually works.
Think big. Start small. Integrity first. Value shipped.
No theatre. No black boxes. No lock-in.
8–12 weeks

From kickoff to production system. Not a demo, a working system on your infrastructure.

20+ years shipping ML100% IP ownershipNo vendor lock-inYour infrastructure