SaiSpec is a governance-first runtime for AI agents. It enforces permissions, accountability, human oversight, and auditability at the moment an agent attempts to take an action.
AI agents increasingly act on behalf of users — calling tools, modifying systems, and triggering irreversible changes. Most frameworks optimize for capability, not control.
Reading data and deleting data are treated as equivalent actions. Systems lack escalation paths for high-risk decisions.
Agents are trusted implicitly. Permissions are assumed, not enforced at execution time.
When something goes wrong, there is no clear record of why an action happened or who approved it.
SaiSpec is available as a Python library you can wrap around any agent loop to introduce governance without changing how your agent reasons.
Actions are explicitly classified by impact: informational, advisory, decisive, or irreversible.
Role-based permissions are checked before tool execution, not after failures.
High-risk actions require explicit justification. Missing reasoning blocks execution.
Irreversible actions are stopped unless a human explicitly approves them.
SaiSpec produces structured, inspectable timelines instead of opaque logs.