Concrete over magical
Product proof uses readable actions, decisions, entities, evidence records, and explicit labels.
Company
Pavri exists to make AI agent action accountable.
Enterprises are moving agents into workflows where actions matter. Pavri is building the security and control plane that makes those actions attributable, governable, and investigable.
Pavri builds security and control for enterprise AI agents by connecting agent identity, action context, policy decisions, evidence, and response workflows.
Thesis
The security boundary is the moment an agent acts.
Security must know who or what is acting, what context matters, which operation is requested, what policy decides, what evidence remains, and what response follows.
Calm control
The system favors structure, precision, and defensible claims over fear-based marketing.
Human accountability
Owners, users, approvers, and analysts remain visible in the workflow.
Operating principles
Pavri is built for security teams that need accountability, not theater.
The company story should earn trust without pretending that every proof point exists on day one.
Name the actor
Every useful control starts with a durable agent, assistant, owner, user, endpoint, or runtime identity.
Name the action
Pavri describes concrete operations such as tool calls, MCP actions, repository changes, credentials, destinations, and commands.
Keep the evidence
Investigation should preserve the path from request to policy decision to response record.
Talk to Pavri.
For buyers, partners, candidates, and press inquiries, use the contact path.