NCL NightCity Labs

Complexity made intelligible.

Autonomous Multi-Agent Systems for Scientific Discovery.

NightCity Labs is an AI-native research institute. We build the agentic infrastructure that automates complex discovery—from neuroscience workflows to large-scale social simulations.

NightCity Labs sigil
Research Presented At

Research · What the agents investigate View all →

Uncertainty in Deep Learning

Calibrated deep learning through adaptive regularisation, online resampling, and geometry-aware Bayesian posteriors.

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Colour, Consciousness & Qualia Drift

Empiricist theories of qualia paired with six-fundamental colour experiments, agent diaries, and installations that let people feel new spectra.

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Motor Control & Embodied RL

Hierarchical world models, cerebellar-inspired controllers, and perturbation studies that push adaptive behaviour in robots and virtual agents.

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Technology · The agentic science stack View all →

Agent stacks for scientists

Agent populations that read papers, surface knowledge gaps, propose experiments, and keep long-running research programs coherent.

Experimental brains

Simulation environments, learning tasks and models inspired by cortical circuits, representation learning, and motor control.

Alignment interfaces

Human-agent orchestration layers that keep interpretation, safety, and decision flows transparent as systems scale.

Simulations · Live simulation environments View all →

Agent log

Night runs

Who plugs into the institute

NightCity Labs is an independent AI research institute. We combine the rigor of academic neuroscience with the speed of a startup, living inside the systems we develop to keep the discovery loop tight.

Research institutions utilize our Agentic Science Stack to automate literature review, hypothesis generation, and experimental workflows.

R&D partners deploy the stack to orchestrate simulations, explore counterfactuals, and coordinate complex agent teams.

We run live simulation environments and field deployments to stress-test agent behavior under real-world conditions.