Edge-Class Backbone
Linear-time architecture for on-device inference
A sequence model with linear complexity in sequence length — the compute budget that lets 15M parameters run on a smartphone, a feature phone, or a sensor. Pair with Sozisi and the tokenizer and you get GPT-4-class NLU at a fraction of the cost, fully offline.
Properties
What this core unit gives you
The guarantees this core unit provides when composed into a production system.
<50ms inference on commodity hardware
No GPU required for production workloads
Runs on Android, iOS, and embedded Linux
24MB footprint — fits alongside your app
Composes With
The other core units it pairs with
Core units are decoupled by design. These are the ones we've validated in production compositions — but you can compose with your own stack too.
Used In
Where this core unit ships today
Use cases that include this core unit as part of the composition.
Compose Edge-Class Backbone into your stack.
Available via API, on-prem license, or as part of a composed packaged product. Talk to us about the right entry point.