Use Cases
Wherever autonomous AI agents run inside your enterprise.
Finance, legal, IT operations, and more -- every team deploying AI agents needs governance. The specifics of what needs bounding differ by department. The mechanism is the same.
Financial Operations
Financial operations: agents that touch sensitive data deserve a short leash.
AI agents doing AP reconciliation, expense auditing, or data extraction from financial systems can access more than they need if their scope is not explicitly constrained. A reconciliation agent that can read one ledger system does not need write access to any external endpoint. An expense audit agent reviewing historical records does not need access to live payroll data.
Arrakis enforces read-only permissions outside defined audit windows, limits access to approved ledger APIs only, and blocks any external data egress that was not pre-authorized. Every action is logged with enough context for your internal controls process.
Policy pattern: resource_scope: approved-ledger-apis only; action: api_read, file_read; denied: api_write, external_post; time_window: business_hours; default_deny: true
Read-only outside audit windows
Agents are blocked from any write action unless they are operating within a pre-configured audit session. Accidental or injected writes surface immediately.
Full audit trail for internal controls
Structured log of every agent data access, exportable in formats your finance compliance team can attach to SOX or internal audit evidence packages.
Legal and Compliance
Legal and compliance: agents that review contracts need bounded context.
Contract review agents and compliance check agents typically need access to document stores and reference clause libraries. They do not need access to HR systems, financial records, or external APIs. Without explicit permission boundaries, an agent told to "review this contract" can follow tool chains that reach far outside the document.
Arrakis limits these agents to configured document stores, prevents external data egress in any form, and captures a full session log for privilege tracking. Legal teams get audit evidence without asking IT to reconstruct what the agent accessed.
Policy pattern: resource_scope: contract-store, clause-library; denied: HR-datastore, finance-*, external_post; session_capture: full; default_deny: true
No external data egress
Contract content stays inside your approved boundaries. External API calls from a legal review agent are blocked by default, not by convention.
Privilege log for legal holds
Every document the agent accessed, in order, with timestamps. Defensible log for legal privilege arguments or regulatory inquiry.
IT Automation
IT automation: infra agents need hard stops on destructive actions.
Agents doing ticket triage, infrastructure diagnostics, or environment management have one failure mode that concerns security teams above all others: an agent that can read environment state today can be told -- or manipulated -- into writing it tomorrow. Without hard policy enforcement at the action level, the boundary is maintained only by the agent's reasoning, which is not a reliable security control.
Arrakis enforces read-before-write policies structurally: an infra agent cannot write to a production environment unless an approval signal is present in the session context. Destructive actions can be blocked entirely for agent categories that have no legitimate reason to destroy state.
Policy pattern: api_write: requires approval_signal in session; prod_env_write: blocked unless manual_approval == true; default_deny: true
Hard stops on destructive actions
Policy-enforced blocks on rm, drop, overwrite, and force-push actions regardless of what the agent's reasoning chain concludes is appropriate.
Approval-gate for prod writes
Production environment writes require an explicit approval signal in the session context. The agent is structurally prevented from acting without that signal present.
HR and Recruiting
HR and recruiting: agents that process personnel data carry compliance weight.
AI screening and outreach agents process candidate PII at scale. The compliance risk is not that the agent does something wrong -- it is that the agent does something untraceable. Which candidates were accessed, in what order, by which session, and whether any data left approved systems: these questions need to be answerable without forensic reconstruction after the fact.
Arrakis enforces anonymization scope (the agent cannot see full PII fields it does not need), limits cross-system writes, and prevents exfiltration of candidate data to external APIs. Every session produces a structured record of data accessed.
Policy pattern: pii_fields: anonymized_subset_only; denied: external_post, cross-system-write; data_egress: blocked; session_capture: full
Anonymization scope enforcement
Policy limits which PII fields the agent can access. The agent receives the anonymized subset it needs for its task, not the full candidate record.
PII exfiltration prevention
External API calls carrying candidate data are blocked at the action level. Compliance teams have a clear record of what data stayed inside your systems.
Tell us about your agent deployment.
We walk through what governance looks like for your specific agent types and the compliance requirements your team is working against.