AXQ
System Architecture
Frank is a multi-agent reasoning system designed to coordinate complex workflows across AI, automation, and cloud environments. It holds context across multiple domains and orchestrates decisions between them.
01. Multi-Agent Orchestration
Domain agents report into a coordinating layer that manages context and decision flow.
02. Persistent Memory Model
A memory model that persists context between runs, ensuring continuity across cycles.
03. Reasoning Loops
Reasoning loops nominate one action per cycle, parking the rest in an inbox.
04. Single Entry Point
A single entry point with scheduled runs, drafting, and health checks.
05. Cost Constraint
Cost per run treated as a hard design constraint, defining the architecture early.
Three Lessons from Building AI
Cost per run is a product decision
It defines the gross margin and the architecture long before the P and L. A product that is too expensive to run cannot be a viable partner offering.
The gap between demo and dependable
Agents fail quietly, returning plausible results rather than nothing. This changes how you scope a pilot and what you promise a partner.
Retention is the whole argument
Products embedded in a partner's delivery survive. Products that sit beside the work as an optional tool do not.