Active research
Stamen
A biology-first compute substrate for post-transformer cognition.
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Research · Mnemo bridge
Technologies
The substrates, architectures, and models behind ReasonLoom
ReasonLoom is rebuilding the stack underneath AI — from biology-first compute substrates and curvature-native silicon, through structured memory and a non-transformer cognitive architecture, up to the models that run on them.
Substrate
A new floor for cognition
Compute substrates and silicon designed around the same primitives our cognitive systems use.
Cognitive
Architecture and memory above the substrate
A non-transformer cognitive architecture organized into engine families, paired with composable durable memory.
Active research
Penelope
A non-transformer cognitive architecture organized into five engine families.
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Research
v0.2
Mnemo
Composable, durable memory bridging cognition and production systems.
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Research · Enterprise preview
Active research
Atelier
A developmental trainer for cognition substrates — grounding, not memorisation.
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Research
Models
Models trained on the ReasonLoom stack
Post-transformer and continual-learning models that exist because the substrate underneath them does.
RL-X1
Flagship post-transformer model trained on the ReasonLoom substrate.
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Research
Research preview
Loominum™ 1.0
One architecture on a continuous axis — from perfect recall to sharp attention, tuned per input.
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Research
Research preview
RL-L1
Continuous-time model for irregular signals — small, fast, and time-aware.
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Research
Research context
The work behind the stack
Beyond transformers
Biology-first compute and substrate-native cognition — including the negatives.
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Structured memory
Analogy, counterfactual, compositional binding — measured at the million-entry mark.
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Geometry-native compute
Silicon where the physics and the geometry of cognition are designed together.
Learn more Palestra — a cognitive gym for human–AI collaboration
A debate-and-effort gym where humans and models practise reasoning under live evaluation.
Learn more Emmy — a research orchestrator for any scientific field
A workspace orchestrator that runs reproducible research pipelines across scientific domains.
Learn moreMeasuring reasoning under real constraints
New evaluations for planning, factual humility, tool reliability, and collaborative problem solving.
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Safety methods for agentic systems
Research on oversight, capability boundaries, secure tool use, and robust refusal behavior.
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Resilient training across distributed clusters
Techniques for keeping frontier training stable when compute, data, and teams span continents.
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