AI agents with provenance.
Every team in your organization is deploying AI tools. You need to know what they're doing in real-time, prove it after the fact, and stop them when they cross scope — without saying no to capability. Tymeline gives you AI Employees in your IdP, every action audit-anchored, scope policies enforced at runtime.
AI agents acting without scope. Audits assembled after the fact.
Your organization is deploying AI faster than your security posture can govern it. Each team picks its own AI vendor. Each vendor offers its own audit logs in its own format. When an incident happens, you reconstruct what happened from a dozen different system logs by hand — and the regulatory bodies asking the questions don't care that the integration layer was always going to break.
AI agents without scope.
Most AI tools deployed in enterprise environments today have access to whatever the deploying user has access to. No scope policy, no runtime enforcement, no real-time inspection. When a marketing AI agent can read finance data because the user who deployed it had access, you don't have governance — you have permission inheritance.
Audit reconstruction by hand.
When the security team gets the call — “something happened, walk us through it” — you start pulling logs from Slack, GitHub, Jira, Workday, the AI vendor's console. Each in a different format. Each with its own timestamp clock. Reconstructing the actual sequence of events takes days. The regulator's deadline is hours.
Sector regulations are accelerating.
NIST AI Risk Management Framework. ISO 42001. EU AI Act. Industry-specific regimes for defense, healthcare, finance. The compliance bar for AI deployment is rising faster than most platforms' engineering roadmaps. “We'll add audit logs in Q3” isn't an answer when your auditor is asking now.
The provenance question has no answer today.
When an executive asks “did an AI agent send that” or “who approved that action,” the honest answer in most stacks is “we'd have to investigate.” Provenance — cryptographic proof of who did what, when, and on what authority — is missing from the AI deployment layer entirely.
AI Employees with scope, identity, and cryptographic provenance.
Every Tymeline AI Employee is provisioned in your IdP like a human hire. Scope policies enforced at runtime, not just configured. Every action anchored to a tamper-evident ledger as it happens. You can prove what any AI Employee did, when, on what authority, and within what scope — instantly.
What you control per AI Employee.
For a CISO deployment, the standard pilot is a full security posture review — one AI Employee deployed against one program, with scope policies, runtime enforcement, and audit anchoring all visible from your security console. Eight weeks to operational fabric.
Four shifts in how you govern AI deployment.
These aren't projected outcomes. They're what CISOs describe within the first quarter of running Tymeline as their AI governance layer — what they were defending before, and what they can now actually prove.
Security teams running Tymeline where the auditor is already in the room.
Tymeline is in production with security teams in regulated industries — semiconductor design, identity platforms, document AI under compliance regimes. These deployments don't treat audit posture as a feature. They treat it as the precondition for the platform existing inside the perimeter at all.
In production, Tymeline AI Employees deploy through customer IdPs (Okta, Entra), with scope policies enforced at runtime. Every action streams to customer SIEM in real-time and anchors to a tamper-evident ledger. Sector compliance is met by architecture: SOC 2 Type II + ISO 27001 + GDPR baseline, NIST AI RMF aligned, with ITAR-aware and CMMC-ready paths for defense and regulated semiconductor.
Bring your compliance regimes. Bring your audit questions.
A 60-minute security review specifically for CISOs and security leadership. Bring the regimes you're defending — SOC 2, ISO 27001, NIST AI RMF, ISO 42001, ITAR, CMMC, sector-specific. We'll show you exactly how an AI Employee gets provisioned, scoped, monitored, and audited end-to-end — and how your auditor would interrogate it.