De-risk AI
Place independent controls around consequential AI interactions and actions.
Independent AI governance
AI understands.
SASKI governs.
De-risk AI with enforceable rulebooks and verifiable attestation.
SASKI places deterministic governance around AI interactions and actions. Your AI proposes; your organization’s rulebook determines what is allowed; SASKI records why.
THE EXECUTION BOUNDARYIllustrative flow
AGENT REQUEST
“Issue a $250,000 purchase order to a new vendor.”
A proposed transaction. A separate rulebook decision.
SASKI AgenticRULEBOOK CHECK- Requester authorization
- Verified ✓
- Approved vendor
- Not established ×
- Amount threshold
- Executive approval ↗
Held for approval
Execution paused under the enterprise rulebook.
RULEBOOK → DECISION → ATTESTATION
Built to reduce risk between AI intent and application behavior.DE-RISK / RULEBOOKS / ATTESTATION
The SASKI model
De-risk. Govern. Attest.
Enforce rulebooks
Translate organizational authority, boundaries, and approval requirements into deterministic checks.
Produce attestation
Retain an inspectable record of what was checked, which rule applied, and why the decision was made.
One company. Four products.
One governance architecture.
Four places to apply it.
SASKI Agentic
De-risk agentic applications by enforcing rulebooks across input, proposed actions, and output—with attestation for each governance decision.
Explore SASKI AgenticSASKI SDK
De-risk human-facing AI with rulebooks before and after the model, plus attestation for the resulting decisions.
Explore SASKI SDKSASKI Replay
Test historical interactions and actions against rulebooks, then inspect the resulting governance evidence.
Explore SASKI ReplaySASKI Estate
Apply the same rulebook governance and attestation architecture to AI-enabled smart homes.
Explore SASKI EstateHow it works
AI proposes.
The rulebook decides.
- 01 / PROPOSE
AI interprets the task
The model proposes a response or action but does not authorize itself.
- 02 / GOVERN
SASKI applies the rulebook
Identity, scope, parameters, prerequisites, and approval requirements determine the permitted path.
- 03 / ATTEST
The decision leaves evidence
The outcome and applied rule are retained as an inspectable governance record.
SASKI separates AI reasoning from authority, then connects the rulebook decision to verifiable attestation.
See the architecture ↗Attestation by design
A governance decision should leave a record.
Connect what was requested, which rule applied, and why the outcome was allowed, held, or denied.
SASKI pairs deterministic governance with cryptographic decision receipts, giving engineering and review teams evidence they can inspect beyond the model’s explanation.
Replay extends that approach to historical traffic, helping teams examine rulebook behavior before an enforcement rollout.
Explore SASKI Replay ↗Where it fits
Where AI meets consequential work.
AV & smart buildingsIT & network operationsSurveillance & accessHealthcare interactionsEducation & minorsEnterprise applications
Research & practice
Better controls begin with better questions.
What happens before the model?
Our Findings examine infrastructure failures in human-facing AI—from data handling to the gap between a claimed safety action and an executed one.
Read the Findings ↗Built with a public-benefit purpose.
SASKI Institute PBC develops independent governance infrastructure for more accountable AI systems.
About SASKI Institute ↗Start with your use case