CortexLab V8

From local intelligence features to local intelligence infrastructure.

V8 separates execution retrieval reranking tools evaluation and language generation into inspectable components. The goal is not to imitate a frontier cloud model. The goal is to own the stack and measure every layer.

01

Execute

Python JavaScript Bash and SQL run in a separate locked executor container.

02

Index

A persistent graph ANN artifact narrows semantic candidates before reranking.

03

Rerank

A trainable relevance model combines lexical semantic graph ANN exact scope and priority signals.

04

Orchestrate

Agents receive tools from an explicit registry with risk classes and hard timeouts.

05

Evaluate

Benchmarks track intent topic MRR recall and retrieval regressions.

06

Generate

An internal llama.cpp service can host a local GGUF small language model.

agent tool registry

Autonomy only through named tools.

read

hybrid.retrieve

Retrieve grounded CortexLab evidence

1800 ms timeout
compute

ann.search

Search persistent-style ANN knowledge graph

1000 ms timeout
read

knowledge.lookup

Look up exact local concepts

600 ms timeout