Discover and classify
Surface sensitive information and apply policy-driven handling requirements across workflows and environments.
How CharliAI helps federally regulated financial institutions move from policy statements to enforceable controls, accountable workflows, and defensible proof.
OSFI scrutiny around sensitive data is increasing, especially where legacy production data remains in UAT, test and other enterprise environments, where approvals and exception handling are manual, and where institutions cannot easily demonstrate operational evidence. CharliAI helps institutions turn governance into execution by applying runtime controls, monitoring data handling, and producing evidence that controls actually operated.
Sensitive data remains in UAT, test and other enterprise environments longer than intended
Data handling approvals and exceptions are often managed manually
Control execution is fragmented across teams, systems and vendors
Institutions can describe policy, but struggle to prove operational evidence
Supervisory findings increasingly focus on governance, protection and remediation
Institutions should identify, classify and protect structured and unstructured data, and perform periodic discovery scans to detect deviations from standards and controls.
Effective data risk management requires governance, lineage, classification, protection, and response processes throughout the data lifecycle.
Sensitive data should be protected at rest, in transit and in use, with controls and escalation mechanisms for unauthorized access.
Surface sensitive information and apply policy-driven handling requirements across workflows and environments.
Support anonymization, masking or tokenization, encryption, and protected handling patterns to reduce sensitive-data exposure across production and non-production environments.
Apply delegated approvals, conditional access, and human checkpoints where policy requires them.
Capture forensic traces, evidence of decisions, exceptions, and auditable records that support regulatory reporting documentation.
A practical control-plane approach for sensitive data governance, enterprise data remediation, deep enterprise integration, and defensible regulatory evidence.
Many institutions already have policies, tools and review processes in place. The challenge is operational consistency. CharliAI connects approvals, policy conditions, runtime control, exception handling, protection workflows, and evidence into a single accountable operating layer.
Identify, classify and protect sensitive data
Policy-driven data controls, protected data handling, runtime enforcement, and integration with existing protection technologies
Consistent control of sensitive information across business processes and environments.
Sensitive data across production, UAT and test environments
Conditional access, anonymization and remediation workflows, exception tracking, and accountable approvals
Reduced exposure and clearer governance across enterprise data use.
Limited lineage and weak evidence of process
Forensic traces, audit replay, evidence packages, and regulatory reporting documentation
Demonstrable proof that controls operated and exceptions were governed.
Manual exception handling and fragmented accountability
Delegated authorization, human-in-the-loop checkpoints, and role-based decision control
Clear ownership, governed overrides, and traceable accountability.
Slow detection of deviations or risky handling
Active surveillance, alerts, behavioral monitoring, and intervention triggers
Faster remediation and stronger operational resilience.
Non-production environment remediation
Sensitive data handling
across AI and workflow
automation
Exception approval
and evidence
management
Legacy data minimization
and controlled access
CharliAI works with existing security, data, workflow, and oversight investments rather than replacing them. CharliAI complements DLP, masking/tokenization, encryption, IAM, workflow, and audit processes.
MicrosoftIdentify pressure points, sensitive data exposure, approval gaps, integration points, and evidence weaknesses.
Apply control points, approval logic, protection workflows, monitoring, and traceability in the target workflow.
Produce defensible evidence, accelerate remediation, support reporting, and expand to adjacent use cases.