How NeuraFrame works

NeuraFrame sits around existing models and workflows. It preserves verified work and decides whether to reuse, review, escalate, or invoke the model. The same frame is the reuse engine in Studio, a drop-in Gateway in front of any provider, portable memory on a robot with Embodied, and curated learning across machines with Fleet.

Input Verified memory Route Model if needed Result Correction Future behavior

Works with existing models

NeuraFrame™ does not require you to replace your model. It can work around local language models, vision models, document workflows, and repeated AI processes.

Teachable over time

Prompting gets a response. Teaching changes the future response. Corrections can become future behavior rather than disappearing into a chat history.

Reuse where safe

Repeated or previously resolved work can be reused when the system has enough confidence. Uncertain cases can still go to the model or route for review.

Edge to data center

The same layer runs on a single Jetson at the edge or a multi-GPU x86_64 server in your data center. The more expensive your model calls, the more it saves, so it scales up with your hardware, not only down.

Pass-through safe

If NeuraFrame™ is not licensed, it can enter pass-through mode. Your model still runs directly, but the reuse and routing layer is disabled until renewal.

The same frame, four products

Studio

Reuse verified work in front of your local model. Docs

Gateway

A one-line drop-in in front of any provider. Docs

Embodied

Ship the learned memory to a robot, no model on board. Learn more

Fleet

Curated round-trip learning across many devices. Docs

What it is not