smaller models, smarter architecture
We're exploring efficient, on-device AI that doesn't require massive compute.
bigger models hit a wall
The Illusion of Thinking
Recent Research, 2025Frontier LLMs show "complete accuracy collapse" on complex reasoning tasks, regardless of model size or compute. They pattern-match training data rather than genuinely reason... throwing more resources at the problem shows diminishing returns.
Centralized by Necessity
Today's frontier models require massive data centers because the industry believes scale is the path forward. Your data feeds ever-larger models that still fail at genuine reasoning.
Privacy as Afterthought
When the goal is "bigger," privacy becomes an obstacle. Centralized training on massive datasets means your information is collected, stored, and analyzed at scale.
Diminishing Returns
Research shows frontier models hit fundamental limits... yet the industry continues down the same path, demanding more data and compute for marginal gains.
Architecture Over Scale
If scaling hits fundamental limits, the answer isn't bigger models... it's smarter architectures. We're exploring efficient systems that run locally, respect privacy, and solve problems current LLMs can't.
Efficient Local Models
Compressed, optimized architectures that run on your devices.
Hybrid Reasoning
Combining neural approaches with symbolic methods... bridging the gap where pure pattern matching fails.
Privacy by Architecture
Federated learning, on-device processing, and minimal data requirements... not as constraints, but as features.
The industry's obsession with scale has created models that devour data and computation while hitting fundamental reasoning limits. We believe there's a better path: efficient architectures that solve real problems, run on your hardware, and don't require surrendering your privacy.
Join Us
We're in the early stages of exploring alternatives to the industry's scale-first approach. If you're a researcher, engineer, or partner interested in efficient, privacy-preserving AI, we'd like to hear from you.
Get in Touch