Kuriom evaluates the complete intended sequence of AI agent actions as an indivisible unit — against your organization's validated knowledge foundation — before any action executes. The result is a cryptographically signed authorization record that exists before any consequence does.
Two or more individually authorized AI agent actions combine to produce an outcome the governing organization never authorized. No existing governance mechanism evaluates the combination as a unit before any action executes.
Regulations require logs that enable reconstruction of the circumstances leading to any AI output. Post-hoc logs document what happened. They do not constitute evidence that governance was applied before the AI acted.
Before any AI agent reaches an execution decision, an information environment has already been shaped — context filtered, alternatives ranked, risk summarized. If that environment was not governed, the execution-time check is working from a compromised foundation.
Existing governance frameworks evaluate individual action permissions. Kuriom evaluates whether the combination of actions the AI agent proposes — as a complete, indivisible sequence — is authorized against your organization's validated knowledge foundation.
The authorization record is produced before the first action executes. It is cryptographically signed, immutably logged, and independently verifiable — without the controller's cooperation.
See How It WorksThe organizational knowledge foundation — validated, versioned, hash-keyed. The reference against which every sequence is evaluated.
The five-condition evaluation. Every sequence is evaluated as an indivisible unit before any action executes. Deterministic. Binary. Auditable.
The immutable governance ledger. Pre-execution authorization paired with post-execution evidence in a single, independently verifiable record.
Requires logs enabling reconstruction of circumstances leading to any output, and transparency about the knowledge the system was acting on. Both require records that preceded the output.
Deployer-side governance — what organizations must demonstrate about how frontier models were authorized to act in their specific workflows — is outside the RAISE Act scope. That gap requires architectural governance.
Requires disclosure of the purpose of AI use and the manner of use. Two distinct disclosure objects. Both require a pre-execution record that existed before the AI acted.
Requires federally regulated financial institutions to maintain model inventory and demonstrate lifecycle governance. The pre-execution authorization record is the evidence that governance was applied before the model acted.
Kuriom is AI-model agnostic and has no commercial agreements with any AI vendor. The architecture operates above the model layer — governing the sequence of actions any AI agent proposes, regardless of which model produces them.