Governed knowledge, kept separate from the models that learn from it.
These are the design objectives of the architecture. Where an objective is not yet fully implemented, it is stated as an objective — not as a shipped capability.
Where a piece of knowledge came from, and what it may be used for, travels with it.
Conflicting evidence is preserved rather than averaged away or silently resolved.
Knowledge outlives any single model — it is not lost when a model is retrained or replaced.
Consequential outcomes stay subject to human review, with the reasoning on the record.
A standards company has an evidence problem worth researching.
PEGS scores assets on evidence, keeps tamper-evident records, and holds knowledge that has to stay attributable years after it was captured. Akashic AI is the research line that takes that problem seriously.
It is research and development, not a released service. Integrations into PEGS surfaces are described here only once they are deployed and verified.
Make a research enquiry. Demonstrations, downloads, and commercial access are published when those offerings are evidenced and ready — not before.
Akashic AI does not certify anything, does not guarantee truth, and does not demonstrate general intelligence. Parts of the architecture are documented design rather than implemented control.
Documented design, implemented control, independently evaluated capability, and released service are four different things, and we keep them apart.