Identity & access
SSO, environment segregation, roles, and permissions to define who can access and execute each action.
Control. Audit.
Trust.
AI only becomes enterprise infrastructure when it can be controlled, audited, and trusted. Governance is part of every execution.
Security from
the first layer.
Identity, data protection, autonomy limits, and execution evidence make up the operational architecture.
Demonstrate how, why and under which controls AI operated.
Six pillars.
End-to-end control.
Data protection
Anonymization, pseudonymization, retention, and protection of sensitive data, with entity recognition in Portuguese.
Autonomy limits
Guardrails, validations, and human oversight keep agent actions within authorized policies.
Audit & traceability
Logging of sources, decisions, versions, models, and interactions to demonstrate how AI operated.
AI security
Controls against prompt injection, information leakage, and tool misuse.
Compliance
LGPD, internal policies, and accountability built into the operational design.
Privacy in
the Brazilian context.
Entity recognition in Portuguese, anonymization, pseudonymization, and sensitive data protection support operations aligned with LGPD and internal policies.
Observability
for trust.
AI Ops tracks quality, cost, latency, drift, robustness, and behavior. Sources, models, versions, and interactions form the audit trails.
Explore AI Ops ↗Let's discuss your controls.
Talk to the team about your operation's security, privacy, and governance requirements.
Talk to a specialist ↗