TeamIDE Labs

Applied AI research. Building inference, training, and systems infrastructure from the ground up.

Foundry

Pure C machine learning framework. Zero external dependencies, full tensor operations, quantization, and training. From bare metal to desktop.

Inference Engines

Hardware-aware inference across heterogeneous accelerators. Running language models efficiently on commodity hardware without GPUs.

Distributed Training

Training language model adapters across commodity laptops with zero inter-node communication. Published research on the Research page.

Memory Systems

Extended context and retrieval systems for language models. Multi-tier memory architectures that keep RAM bounded while enabling long-horizon reasoning.

AI-Native OS

Operating systems that boot directly into AI inference. From UEFI bare metal to full runtime. No Python, no Docker, no cloud.

Model Architecture

Novel hybrid architectures combining recurrent and attention mechanisms. Exploring how architectural choices affect hardware utilization and memory efficiency.

Read our published work on the Research page.