Purpose Kernel
Each agent has a mission, boundaries, authority, escalation rules, and success metrics.
Perlis gives teams always-on AI agents with governed memory, policy-bound autonomy, auditable tools, and collaborative sub-agents built for real enterprise operations.
Planned a safe delegation, routed sub-steps through policy, and kept the run auditable.
Prompts and tool inputs are redacted before providers or adapters see them.
Delegated invoke steps still pause when policy requires human review.
Parent and child events share a request id for inspection in the portal.
{
"result": "completed",
"agent": "core_orchestrator",
"steps": 1,
"proof": "hash_chained_audit"
}
The gap
Who approved the action?
Which data did it use?
What tool permission did it have?
How do we roll it back?
Platform pillars
Perlis combines memory, identity, policy, tools, workflows, and audit into a system designed for enterprise-grade autonomy.
Each agent has a mission, boundaries, authority, escalation rules, and success metrics.
Persistent context that is scoped, permissioned, inspectable, and deletable.
Manifested capabilities, policy checks, dry runs, approval gates, and auditable execution.
Create supervisors, specialists, reviewers, sentinels, builders, and archivists.
Every meaningful action records actor, evidence, policy, data, result, and rollback path.
Perlis proposes improvements from repeated work, then tests and reviews before promotion.
How it works
Perlis separates reasoning from authorization. Agents can propose actions, but policy, approvals, tool schemas, and audit happen outside the model.
That means autonomy becomes something teams can manage instead of something they have to nervously vibe-check.
Agent roster
Decomposes requests into governed sub-agent steps and links parent/child audit events.
LiveDetects anomalies, estimates savings, drafts tickets, and asks before making changes.
Live sliceCorrelates alerts, logs, deploys, and ownership into an actionable incident timeline.
Live sliceFuture reviewer for risky actions, prompt-injection patterns, policy drift, and excessive agency.
PlannedSecurity model
Perlis gives security and platform teams a control plane for agent identity, tool permissions, memory scopes, policy decisions, audit logs, and kill switches.
Integrations
Start with the systems technical teams already trust: cloud billing, alerts, tickets, code, chat, and observability.
Design partners
We are looking for technical teams that want secure agents for DevOps, cloud cost, incident response, workflow automation, and enterprise knowledge operations.