We build intelligence that does more with less.
We investigate the full path from model to machine: architecture, inference,
context, and the consumer hardware that brings AI into everyday life.
Efficient models
Sharper architectures and inference systems that preserve capability without wasting compute.
Consumer hardware
AI designed to run privately and quickly on phones, laptops, and the devices people already own.
Context systems
Structured memory and dependable context that keep every token useful from prompt to result.
Real-world measurement
We measure latency, throughput, energy, and reliability where intelligence actually gets used.
Notes from the work on efficient models, practical systems, and hardware that lets intelligence travel further.
