GPU-aware model manager
inventory-aware placement chooses GPU hybrid or CPU serving and recommends quantization based on model size and available VRAM.
CORTEXLAB V9
local intelligence becomes an operating platform.
V9 connects models datasets isolated execution retrieval agents evaluation and observability into one governed local AI engineering system.
LoRA + quantization pipeline
versioned datasets feed adapter-training plans then evaluation gates and quantized GGUF export.
container-per-job execution
every submitted program gets a fresh disposable runtime container with no network hard resource limits and automatic cleanup.
persistent vector database
192D vectors are stored in segmented collections that survive application restarts and support targeted segment probing.
multi-agent supervisor
researcher critic teacher and engineer specialists operate through a permissioned tool registry and expose their evidence.
observability + evaluation
telemetry traces benchmark runs dataset versions model jobs and retrieval quality become first-class operational signals.