CONTROL. CONNECTIVITY. CLARITY.
The Context Layer for governing Agentic AI & Model Decisioning.
+47%
4 in 5
rise in AI-enabled cyberattacks in 2025.
IBM Cost of a Data Breach 2025
organizations do not have a mature governance model for AI agents.
Linux Foundation, 2026
$12.9M
average annual cost of poor data quality, the foundation every model and AI decision is built on.
Gartner
ONE PLACE TO SEE HOW EVERY DECISION CONNECTS
Celine: Move the context layer picture in this section
WHAT BREAKS IN SILOS. WHAT CONNECTION FIXES. Greg: Please come up with a better headline
Systems that don't talk
Loan origination, KYC, models, and controls each run in their own tool. Risk moves between them; proof doesn't, so approvals slow and hand-offs break.
One unified context layer
Auditrol connects every system, control, and model into one graph. Each becomes a node you can trace end to end, so hand-offs stop breaking and nothing moves without a record.
No proof until it's too late
By the time an audit or incident asks, the trail is cold and the rationale lives in someone's head, not the system.
Any decision, provable in seconds
Because lineage and control logic live in the graph, you see how any decision was reached on demand: the data, the model, and the rationale in one view, not a forensic hunt.
Stalls, restarts, slipped deals
Agentic AI freezes before production, audits restart from zero every time someone leaves, and cycles stretch while deals slip. The exposure compounds quietly.
Continuous assurance, not fire drills
The fire drill goes away. AI ships with a provable trail, every audit builds on the last instead of starting over, and what your team knows stays with the company when people leave.
USE CASES
RESULT
ONE LAYER, EVERY CONTROL
Context Layer
Predictive Risk Insights
Always-current visibility across regulations, controls, models, data, and owners.
Control Rationalization
Eliminates duplicate controls and closes regulatory coverage gaps.
Model Governance
Single inventory, lineage, and compliance reporting across first- and third-party models.
AI Governance
Full inventory and policy monitoring across LLMs, agents, and data usage.