Graphicle
Code graph and memory for your coding agents, in one Rust program. It maps your repository, remembers your project's docs, decisions and past sessions, and returns cited excerpts.
Explore GraphicleAI research & development
Building AI
with a longer
memory.
We build open-source tools, Graphicle for coding agents and JLA for linear attention in JAX, and research memory inside the language model with CIEL.
What we build
Two open-source tools, one research program.
Graphicle gives coding agents memory today: a code graph and your project's docs, decisions and past sessions, on your machine. JLA brings fast linear-attention kernels and a training stack to JAX.
CIEL is our foundational research: long-term memory that lets a small language model recall facts far beyond the length of text it was trained on.
JLA
Fast linear-attention kernels for JAX on NVIDIA Hopper: Mamba-2 and Mamba-3, Gated DeltaNet, KDA, RWKV-7 and GLA, with a full training stack. It trains a 1.3B transformer at 72.3% MFU in FP8 on one H100.
Explore JLACIEL
Long-term memory for language models. In synthetic recall tests, our 350M-parameter model recalls facts from documents up to 1M tokens long, after training only on documents of up to 8K tokens.
Explore CIELGet startedWork with
Work with
us.
Install Graphicle and your coding agents get its code graph and memory today. To collaborate on CIEL research or our open-source projects, get in touch.