CCAIE publishes its frameworks so that clients, partners, and professions can evaluate the method before they evaluate the vendor. Published frameworks are held by the CCAIE Foundation and are vendor-neutral by design.
Six principles for governing multi-agent AI systems so that accountability survives automation. Architectural rather than behavioural; designed to be instantiated per profession or sector. CCAIE Foundation Framework Document v0.1.
Five maturity levels across three governance domains, from a peer-reviewed paper: where an organisation's generative-AI governance actually stands, and what the next stage would require. Summarised with the primary source linked and the unfinished part named.
A structured method for finding where AI creates measurable value in any organization: map functions to value drivers, score by value and feasibility, screen for data readiness and responsible use, and pick the right first project.
Working patterns for building multi-agent systems that satisfy the Octopus Protocol's criteria — provenance, confidence declaration, audit records, and human accountability boundaries. In development, published as they mature.
These frameworks are grounded in delivered work. Read the case study of our executive AI programme at an industrial holding — including the measurement finding that shaped Principle 6 and CCAIE's entire service model.