For anyone curious about what I mean by “substrate” in this context - this isn’t an agent framework or wrapper around a single LLM.
CMPSBL is operating more like a cognitive OS: it provides persistence (memory), observability, defense, multi-model routing, and a self-improvement cycle for AI systems.
The goal isn’t clever chat output; it’s continuity, coordination, and the ability for a system to reflect on its own performance and update itself over time.
The v5.5.0 drop includes the full technical docs + module specs + validation methodology + runtime evidence.
If you want to audit how the substrate works or decide if this class of architecture makes sense, that’s the best place to start.
Main intended use cases today are:
– research labs
– cognitive infrastructure work
– autonomous systems R&D
– embedded AI runtime projects
– multi-model coordination
– memory-centric applications
Open to licensing discussions with research groups and R&D labs.
For anyone curious about what I mean by “substrate” in this context - this isn’t an agent framework or wrapper around a single LLM.
CMPSBL is operating more like a cognitive OS: it provides persistence (memory), observability, defense, multi-model routing, and a self-improvement cycle for AI systems.
The goal isn’t clever chat output; it’s continuity, coordination, and the ability for a system to reflect on its own performance and update itself over time.
The v5.5.0 drop includes the full technical docs + module specs + validation methodology + runtime evidence.
If you want to audit how the substrate works or decide if this class of architecture makes sense, that’s the best place to start.
Main intended use cases today are:
– research labs – cognitive infrastructure work – autonomous systems R&D – embedded AI runtime projects – multi-model coordination – memory-centric applications
Open to licensing discussions with research groups and R&D labs.