Help build a new kind of computing system.

Built by the Founders

Qognetix began as an exploration of biologically inspired neuron architectures and signal-driven computation. Early work by Des Atkins demonstrated that persistent signal dynamics could reproduce biologically plausible neural behaviour in software.

Recognising the broader implications of this approach, Nic Windley founded Qognetix to develop the concept into a structured Synthetic Intelligence platform capable of supporting governed intelligent systems operating within real-world infrastructure.

If you’re curious about the origins of the platform and the people behind it, you can learn more on the Team page.

→ Meet the founders

The Problem

Modern AI systems are powerful but fundamentally limited.

Most current systems rebuild decisions through repeated inference over static model weights.

They are expensive, opaque, and difficult to govern when embedded inside real-world infrastructure.

As AI moves into:

• energy systems
• transport networks
• industrial automation
• safety-critical engineering

these limitations become structural problems.

What We Are Building

Qognetix is developing a new computing paradigm: Synthetic Intelligence.

Instead of treating intelligence as a statistical prediction engine, we are exploring systems where behaviour emerges from interacting signal substrates inspired by biological nervous systems.

Our platform, BioSynapStudio, investigates how intelligence can arise from:

• excitable membrane dynamics
• ion channel interactions
• signal propagation
• persistent stateful systems

Rather than repeatedly recomputing outputs from model weights, intelligence evolves continuously within a governed runtime environment.

This is closer to building a digital nervous system than training a model.

Why This Is Hard

We are building systems that involve:

• real-time simulation
• thousands of interacting components
• complex stateful dynamics
• long-running execution environments
• visualisation of internal behaviour

These systems behave more like physics engines or biological simulations than traditional applications.

Many problems we encounter do not yet have established engineering patterns.

Who Thrives Here

The engineers who enjoy this work tend to be people who:

• build things simply to understand how they work
• enjoy debugging complex behaviour
• care about architecture and performance
• are curious about systems, physics, or computation
• prefer foundational engineering over feature work

Many of our favourite engineers have built things like:

• game engines
• emulators
• compilers
• simulation environments
• operating systems
• strange personal experiments

Who Might Not Enjoy It

Early-stage deep tech is not for everyone.

You may not enjoy this environment if you prefer:

• large teams and highly specialised roles
• predictable product roadmaps
• narrowly defined feature work
• heavy reliance on frameworks

Early engineers at Qognetix are generalists working close to the system itself.

We are currently a small team building the first generation of the Synthetic Intelligence platform. Early hires will work directly with the founders and help shape the architecture, tooling, and engineering culture of the company.